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4 Sensors Introduction Although many factors contribute to the success of any military operation, it has long been recognized that information is one of the most important—information in many different forms and acquired on many different time scales. Information During conflict situations several different kinds of information come into play. At the highest top-down level is situation awareness. Warfighters must understand everything that they can about the nature of the opposing forces—their current positions, their movements, their composition, their infrastructure, their capabilities, their communications, their weapons, their threats, their plans. The more the better—in real time on a scale that ranges from minutes to hours—and not what they were doing a day ago, but what they are doing right now. Obviously, for maximum cooperative effectiveness the United States ought to have the same complete picture of its own forces, distinguishing accurately between friendly and adversarial forces to minimize or eliminate friendly-fire incidents. To complete the scenario, an accurate, real-time picture of the environment is needed—e.g., the details of the terrain, the current and anticipated weather or sea conditions, the presence or absence of mines, and so on. Generally, in real conflicts, only a few of these factors are actually known to the degree desired—knowledge of some may be stale and out of date, and other factors may only be guessed at and some completely unknown. The better the job U.S. forces do in
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achieving valid situation awareness, the larger the potential competitive advantage they can enjoy. On a shorter time scale, from the bottom-up point of view, effective utilization of weapons requires detailed and timely—fractions of seconds to minutes—information about both the targets and the weapons themselves. Targets must be recognized as such, their positions localized instantaneously, their motion measured to high precision, their most vulnerable aim points identified, and so on. Similarly detailed continuous information about the weapons is needed to aim or guide them to a successful interception of target—e.g., weapon position, inertial parameters (such as orientation, velocity, and acceleration), and environmental parameters (wind and tidal currents). On a much longer time scale, outside actual combat situations, information is needed in several forms to provide for such necessities as equipment maintenance and support and overall logistics. For example; it is necessary to know what has failed or is about to fail, or what the weather will be tomorrow. Sensors To acquire desired information, measurements of all kinds of physical parameters must be made. The devices that permit these measurements are known broadly as sensors. The term "sensors" encompasses an enormous range of technologies and devices. Some can be as simple and old fashioned as the direct measurement of a local temperature by means of a thermocouple, and others can be as modern as the detection of a biological agent by a miniaturized mass spectrometer, or as complex as a synthetic aperture radar (SAR) all-weather imaging system. In all cases, whatever the sensor, an interaction between the sensor and its local physical environment results in the generation of some kind of signal, generally a form of electrical response of the sensor's physics, chemistry, and biology to the physics, chemistry, and biology of the outside world. The interpretation of these sensor signals through signal processing, data fusion, and the like leads ultimately to the extraction of the desired information. Sensor Categorization Operational Modes Sensors, whatever information they are attempting to collect, can be broadly classified into two categories of operation, passive and active, which are defined as follows: Passive sensors simply measure and report on, via their response signals, whatever they detect in their local environment. In a sense they just listen. A thermometer and video camera are good examples of passive sensors. Even
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though a passive sensor responds only to local physical phenomena, the information may well be coming from a distance—perhaps in the form of photons of light that travel from the objects or scene of interest and impinge on the sensor's detectors to produce the necessary local interactions. From a military point of view, passive sensors have the great advantage of producing valuable information without emitting any signals of their own that might give away their position and expose them to possible retaliation. Active sensors, on the other hand, typically stimulate the environment by generating and emitting known signals, which propagate out to the objects or targets of interest, interact with them, and reflect or scatter energy back to the sensor, which then responds as in the passive mode. Because the self-generated signals have known properties, it is often possible to use signal processing to extract very weak emitted signals returning from the objects of interest from the inevitable competing noise and clutter-generated signals in the sensor. Although operating in an active mode reveals the location of the emitting source, it is sometimes the only practical way to collect the desired information. The most familiar example is radar. If an object of interest is itself not emitting electromagnetic radiation, the only practical way to provide the desired geometric information about the object's existence, location, motion, size, shape, identification, and the like is to illuminate it deliberately. Although frequently the transmit and receive functions are combined in the same hardware, they do not have to be physically co-located. In the context of radar, this variation or active sensing is known as bistatic; in missile guidance, such a configuration is referred to as semiactive, in that the missile itself operates in a passive mode, whereas the target is actively illuminated by a separate source. Sensors that operate on the basis of wavelike, propagating physical phenomena such as electromagnetic waves, e.g., radar and laser detection and ranging (LIDAR), or acoustic waves, e.g., seismic sensors and sonar, can be operated in either passive or active mode to collect different kinds of information. Sensors based on nonpropagating phenomena such as those that sense chemical compounds or accelerations (initial sensors) operate only passively. Physical Phenomena The range of sensor types of interest to naval forces is enormous. Box 4.1 lists the basic physical phenomena that underlie the types of relevant sensors. As can be appreciated from this list, the subject of sensors is very complex, involving a large number of apparently quite disparate technical disciplines. Generic Sensor Model Each of the physical phenomena listed in Box 4.1 is discussed below in more detail in the context of the current state of the art and projected possible future
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BOX 4.1 Physical Phenomena Underlying Sensors • Electric only • Mechanical Direction Inertial—acceleration, linear and rotational Field strength Gravitational—direction and weight • Magnetic only Flow of fluids Direction Position Field strength Stress and strain • Electromagnetic: active and passive • Chemical High frequency • Biological Microwave (L, S, C, X, Ka, Ku) • Nuclear Millimeter wave Alpha, beta, neutron Optical (IR, visible, UV) • Environmental X-ray, Gamma-ray Atmospheric parameters—temperature, wind, humidity, visibility • Acoustic Ocean parameters—temperature, currents, salinity Air—sound • Time Water—sonar Solids—seismic performance capabilities of the sensor technology associated with each. Although useful for better appreciation of the individual sensors and sensor technologies, this approach can be quite confusing when it comes to projecting the future because of the great variety in sensor types and related details of technology that mask their underlying common features. This section discusses sensing in general and the common concepts and issues that characterize all of sensor technology. Five critical technologies—semiconductor, superconductor, digital, computer, and algorithm technologies—appear to be common to all sensor types, and careful delineation of these greatly simplifies the difficulties of projecting future sensor capabilities. Insofar as it is possible, for each identified common critical technology, quantitative performance projections based on today's historical performance growth patterns are discussed below as clues to future potential. A model of a generic sensor is shown in Figure 4.1. Sensor Interface with the External World The first thing that must be considered is the interface between the sensor and the physical phenomena to be sensed. For some classes of sensors, e.g., chemical or biological sensors, physical samples of atoms or molecules or chunks of material must be collected and inserted into the sensor's detection mechanism. The design of this kind of interface permits a good deal of flexibility and no doubt will vary considerably over time. Sensors such as LIDAR designed for propagating phenomena collect samples
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FIGURE 4.1 Generic sensor model. that are less material in character and more wavelike; e.g., the detected objects are photons or phonons. However, the interfaces for such sensors are highly constrained by the free-space wave-propagating physics of the phenomenon being sensed: Whatever the details of the implementation technology, the sensor interface to the outside world must provide an appropriate wave equation impedance match. The details of the sensor implementations can be altered by the designer, but the outside world's physics is whatever it is and is not under the control of the designer or the sensor. When sensor performance capabilities are projected into the near and far future, the interface constraint remains invariant—e.g., although it will be possible, with time, to compress more and more digital and computing capabilities into ever-decreasing volumes, the dimensions and characteristics of the radar aperture needed for a given task will remain basically the same. Beamwidth requires so many free-space wavelengths across the aperture, and grating lobe suppression requires a certain minimal spacing of elements, again in terms of the free-space wavelength. Certain characteristics of the interface are, and will always be, independent of the technology used to implement the sensor hardware. For sensors—e.g., inertial, gravitational, and time—as the sensors are totally and inextricably immersed in the phenomena to be sensed, the concepts of external world interface and collection are simply moot. Detection Once properly interfaced to the external world, the sensor must selectively detect the manifestations of the phenomena of interest and produce signals that can be used to quantify and convey the desired information. Although in the past many simple sensors used purely mechanical means of indicating the detected signal, as, for example, an automobile thermostat or a thermometer based on the motion of a bimetallic strip or membrane, most sophisticated sensors of interest to the Navy and Marine Corps indicate the results of detection as an electrical signal—a modulated voltage or current. Even though the physical phenomenon being sensed may not be directly electrical in nature, but rather chemical or
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biological or acoustic, the detection is usually accomplished by using the phenomenon of interest to generate or move free electrons, thereby transducing the physical manifestations into electrical signals. For example, microwave signals are detected by causing the associated time-varying electromagnetic fields to induce currents in electrons already available in conducting elements of the sensor. Optical signals generally use the large energy inherent in each photon (E = h) to kick loose bound electrons to create free electrons that are then collected and/or moved to produce measurable charges or currents. Other sensors use mechanical components that move under the influence of the physical phenomenon to be sensed but that are also part of an electrical capacitor or other circuit element so that the resulting motion alters the circuit parameters, thereby modulating an electrical signal in an interpretable way. Chemical and biological sensors use yet other techniques to produce electrical detection outputs. The technology for processing signals that are electrical in form is well understood, and the future capabilities of many diverse sensors can be projected in terms of electrical signal processing technology. Electrical signals are now uniformly dealt with via electronics. Modern electronics is uniformly based on semiconductor technology, and projected progress in semiconductors is often directly translatable into valid projections of improved sensors and sensing. In addition, superconductor technology offers many attractive ways of dealing with electrical signals that operate on the basis of quantum effects that are quite different from those encountered in semiconductors. Although still very much in development, because of the great promise and the recent progress demonstrated, progress in superconductor technology must also be carefully assessed for application to future advanced sensors. Although electrical signals from independent sensor elements are often combined directly today in analog form, increasingly they are converted immediately to digital format. It is virtually certain that this will be the only approach considered in the future because of the many proven advantages of digital technology. Thus, projected progress in digital technology will be directly translatable into projected improvements in sensors and sensing. Information Extraction The stream of digital data emerging from each individual sensor element, e.g., each pixel of an IR focal plane array or each receive element of a phased array radar, must be assembled, stored, processed to extract the desired information, and communicated to a user—sometimes a human and sometimes another mechanical/electronic device—that can use this information for guidance and control or some other purpose. Progress in all aspects of computer technology, and particularly algorithm technology, will translate directly into improved, more capable sensors.
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Relevance: What Do Sensors Do for the Naval Forces? That sensor technology, in its myriad embodiments, is critical to the success of all naval force operational tasks or missions is obvious (Box 4.2). Whenever information is required, sensors are utilized to make the physical measurements from which the desired information is extracted. Radar, optics, and sonar sensors, through the active or passive exploitation of the physics of wave propagation, give information about distant objects that is useful for general surveillance and situation awareness as well as for more specific purposes, such as real-time target location and weapon guidance. Other sensors, such as position-sensing devices or inertial sensors, produce useful real-time local measurements that can be used to control all kinds of platforms, including whole ships, steerable radar or communication antennas, and gun mounts on ships, or even individual missiles in flight, depending on just where the sensors are located. Yet other sensors produce measurements for which the long-term variations in the measured parameters provide the useful information. For example, temperature or atmospheric pressure sensors can supply inputs for short- and long-term weather prediction, whereas acoustic sensors mounted on rotating machinery can provide evidence of bearing wear or imminent gear failure, thus triggering needed repair and maintenance procedures. In short, naval forces are heavily dependent on the use of sensors today, and the future seems to promise even broader use of sensors as the technology continues to evolve toward more capable performance and the demand for more and better information escalates. Future sensors, as compared with existing implementations, promise to cost less, have higher sensitivity and precision, be available in much smaller, lower-power packages, and perhaps be capable of measurements currently unimagined (i.e., be completely new types of sensors). Technology Status and Trends Despite the dangers in attempting to project tomorrow's technology entirely in terms of what we see today, doing so can still impart valuable lessons. Preceding BOX 4.2 Sensor-dependent Operational Tasks and Missions Situation awareness General foe/friend information Surveillance Threat detection, recognition, and localization—general or specific Weapons targeting—offensive or defensive Logistics and maintenance
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BOX 4.3 Technology Trends Common to all Classes of Sensors • Solid-state technology Miniaturization Lower power Integrated circuit manufacturing Integral packaging Microelectromechanical systems • Distributed systems (continued) Data compression Societies of microsensors—sensors plus computers • Atomic-level manipulation—nanotechnology Designer materials Quantum wires and dots • Multidimensional signatures (clutter rejection, detection, automatic target recognition) Multispectral Hyperspectral Data fusion • Digital implementations Analog-to-digital conversion/digital-to-analog conversion Direct digital synthesis Computers and signal processors • Multifunctional sensor systems; common transmit and receive apertures for: Radar Communications Electronic warfare/electronic support measures • Distributed systems and imple-mentations: fault tolerance Networking Data fusion the panel's discussion of the five technologies critical to all modern sensors is a brief review below of the technology trends that are evident in today's developments and that are shared, in some way, by all classes of sensors (Box 4.3). Toward the end of this chapter, the panel speculates on the impact of sensor technologies on tomorrow's naval forces, touching on other possible future directions, not so evident today but desirable from the user's point of view and not obviously incompatible with some law of nature. Solid-state Technology The most obvious overall trend of significance in technology today is solid-state technology's dominant role in both analog and digital electronics. Today's digital circuits are solid-state—the semiconductor transistor, in one form or another, is the workhorse of the industry and the foundation for all practical digital IC implementations. Its one evident competitor, lurking in the background but always gaining grounds, is another solid-state technology—superconductors, e.g., Josephson junctions, superconductor quantum interference devices (SQUIDs), and RSFQ logic.
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Even in the analog world, solid-state technology has come to dominate the audio and video amplifiers in entertainment electronics. In the last decade or so, even the generation of microwave power for radar and communication applications has come to be realized increasingly often in solid-state form. Although many legacy microwave systems still generate RF by means of tubes, all new radars are automatically assumed to be some form of solid-state phased array, and soon the only place tube technology will be found is in microwave ovens. Today, magnetrons are still cheaper than the equivalent power transistor, but that may not last as solid-state electronics continue simultaneously to improve in performance and fall in price. Given this widespread trend, it seems likely that all future advanced sensors will process their detected electrical signals with some form of solid-state circuitry. It can be expected, then, that advanced sensors will share in the continually improving aspects of solid-state technology, that is, increasing miniaturization, higher speeds, decreasing power per function, increasing device density and complexity via IC manufacturing techniques, integral packaging concepts, and decreasing unit costs. A spin-off application of semiconductor manufacturing to three-dimensional micromachining of silicon (Si), enabling the development of MEMS, has already produced a range of novel sensors and actuators with significant performance and cost advantages over the conventional forms. Atomic-level Manipulation One of the most exciting recent technology developments is the growing ability to manipulate matter at the atomic level. Largely because of the efforts applied to the fabrication of solid-state devices and integrated circuits, through mastery of thin-film deposition techniques and the physics and chemistry of surface phenomenon, it is now possible to control material and structural fabrication at the level of the individual atoms. These skills have already been used to create artificial materials with unique characteristics, e.g., alternating-layer semiconductor structures for advanced microwave devices, integrated multilayer Bragg reflectors for photonic applications, magnetic structures with as many as 50 alternating layers of iron and chromium for giant magnetoresistance sensors, biologically inspired self-assembling layered materials of polymers and ceramics with unusual properties, and even artificial high-temperature superconductors with monomolecular layers of alkaline earth atoms (calcium, strontium, or barium) alternating with copper dioxide (CuO2) layers. These techniques allow the tailoring of materials and devices at the nanostructure level,1 i.e., accurate growth and placement of clusters of a few or a few 1 Robinson, E.Y., H. Helvajian, and S.W. Janson. 1996. "Small and Smaller: The World of MNT," Aerospace America, 33(9):26–32, September.
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tens of atoms down to the positioning of single atoms. They will provide completely new sensor materials and the quantum wires, dots, and single-electron transistor devices that are likely to be exploited to continue the long-term growth trends in solid-state electronics into the future for decades to come. It seems clear that sensors and sensor systems of all kinds will benefit from these capabilities, getting continuously smaller and cheaper and more capable with time. The implementation of microscale or perhaps even nanoscale self-contained entities with integrated sensors, computers, and actuators will certainly become possible over the next several decades, and such devices will probably represent a mature, widespread technology by 2035. Digital Implementations Another very obvious characteristic of modern electronic technology is the inexorable march toward all-digital implementations. The significant advantages of digital versus analog implementation in terms of flexibility of processing, error containment, and robustness against drift have long been recognized, but cost, speed, and other obstacles have hindered the conversion in many areas. With the performance and costs of digital computers and signal processors improving exponentially with time, i.e., by factors of 5 to 10 every few years, the obstacles are vanishing and the digital implementation of all sensors and sensor systems in the near future appears inevitable. Analog-to-digital conversion (ADC) technology and its converse (DAC) are currently making such rapid strides in sample rate, number of bits, size, and power, that systems that involve the direct digitization of microwave radar and communication signals at gigahertz rates, with adequate dynamic range and low enough size, power, and costs to be considered practical, are already under development in many places, with field deployments expected in less than 5 years. These kinds of ADC/DAC capabilities, combined with accelerating computational capabilities, will permit the implementation of advanced adaptive processing algorithms, e.g., digital beamforming and space-time adaptive processing (STAP), and effective ATR algorithms, as well as the exploitation of multisensor data fusion techniques. Given the ability to digitize and digitally process almost any radar waveform, it is clear that the time is ripe for the application of digital techniques to other aspects of the system, such as the generation of arbitrarily complex radar transmission waveforms with performance features that go well beyond the simple continuous wave (CW), linear frequency modulation (FM), and occasional phase-coded waveforms that have dominated radar technology to date. Distributed Systems As individual sensor and computing elements grow ever smaller in size, power, and cost and simultaneously more powerful, the temptation to combine a
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large number of them into a super complex of distributed, intercommunicating elements becomes irresistible. The trend today is toward distributed phased-array antennas for radar and communications, multiprocessor supercomputer architectures, distributed power conditioning, the Internet, and so on. And there are enormous advantages to be gained—more information-bearing signals can be collected, more overall computer throughput can be achieved (but always by a factor less than number of elementary processors combined), and much higher overall reliability with graceful degradation characteristics can be obtained. Since it is always possible to make things complicated faster than it is possible to improve the reliability of the individual elements, fault-tolerant redundancy techniques must be explicitly addressed for graceful fail-safe degradation. Equally obvious is the need for efficient, high-bandwidth interelement communications, probably fiber optic and wireless, in which data compression techniques, both lossless and lossy, will come into play. Moreover, as the Internet has shown, information collected from many, perhaps widely dispersed sources, with the proper communications technology and protocols in place, can be profitably correlated to allow a fuller understanding of a subject or situation. Data-fusion and data-compression algorithms will play a key role in the application of these concepts to sensing and to the achievement of the desired battlefield situational awareness, ATR, damage assessment, and related capabilities. An obvious danger lies in the potential flood of data that a capable multisensor distributed data collection system can create. It is possible to generate overwhelming amounts of data that can cause a total shutdown of the human users, whose performance is notoriously nonlinear and prone to catastrophic collapse. (Degradation is definitely not graceful for overloaded humans.) Concepts and algorithms to permit the recognition, extraction, and viewing of only the minimally required information from large distributed databases must be developed—an area of significant future need for research and development. Eventually powerful miniature sensors will be combined in a single package with on-board, integral computational capabilities to form mini-systems-on-a-chip. An intriguing prospect for the future is the notion of interacting armies of small, capable, autonomous entities—microrobots that fly or crawl or swim—that combine miniature sensor packages with integrated computers, actuators, power sources, and wireless communication capabilities. These assemblies might be capable of functioning as ant societies do, with each participant acting locally on the basis of mostly local information, and the whole assembly functioning effectively to reach some global goal. This kind of implementation of sensors suggests the possibilities of higher overall performance in surveillance, for example, through adaptive, autonomous spatial repositioning of the individual sensors. The development of single, small, flying sensors of this sort is already under way. Successful artificial societies of this type will require the development of a deep understanding of what the appropriate rules of behavior should be and their implementation in software—another topic for future R&D efforts.
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MEMS sensing element displacements may some day be implementable with greatly improved sensitivity over the capacitance or resistance noise-limited measurement techniques currently employed. Ultimately one can expect to see the A/D conversion function integrated onto the sensor chip, along with exponentially increasing digital signal-processing and computing capabilities, to produce a self-contained, miniature inertial navigation capability—full navigation, not just sensing—and, no doubt, aided by GPS information, when available. Chemical and Biological Sensors Although sensing chemical or biological substances remotely at a distance is possible through the LIDAR, most chemical and biological sensors rely on direct physical contact between the sensor interface and the unknown or sought-for substance. For detecting known (sought-for) substances, physical matching between the detector and the target substance in the form of atomic or molecular templates, specific responses, or selective chemical reactions is used. This approach can produce conveniently small, cost-effective, sensitive detectors of sought-for target substances but yields no information about a nontarget that may be present. A more fruitful technique for dealing with unknowns is to carry out basic physical measurements of the molecular structure, by optical or mass spectroscopic techniques, and identify the unknowns by pattern matching against the large databases of known material parameters that have been laboriously accumulated over the years. Until recently, it has been sufficient to make these spectroscopic measurements in the laboratory. As a result these classical, physics-based, chemical and biological sensors are often large (e.g., table-top to room-sized), slow (e.g., minutes to hours), and expensive. Tiny Time-of-flight Micromass Spectrometer The threat posed by chemical and biological weapons together with the opportunity afforded by modern optical and digital technology will drive the rapid development of new sensors. Portable, sensitive, fast, inexpensive sensors for chemical and biological sensing are needed for field use today, and development activities in this arena are increasing. The Defense Advanced Research Projects Agency, for one, has mounted a major thrust, emphasizing the detection and identification of biological agents. One of the most sensitive and selective detectors of biological and chemical agents known is the mass spectrometer. DARPA, with Johns Hopkins University's Applied Physics Laboratory, has initiated an ambitious program to develop, in about 5 years, a tiny time-of-flight (TOF) micromass spectrometer. This rugged, fieldable instrument would be small enough (< 5 lb, < 3,000 cm3, < 50 watts) and inexpensive enough (<$25,000) to fly on an unmanned aerial vehicle, would generate data at 10 ms
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per spectra, and would be sensitive down to the single-molecule level and flexible enough to work with solid particulates, chemical vapors, and aqueous materials. Combined with advanced sampling and signal processing, this could provide a major advance in chemical and biological sensing with broad applicability to biological and chemical defense, battle-space management, damage assessment, and intelligence collection. Microelectromechanical Systems Although the tiny TOF micromass spectrometer represents a quantum leap, so to speak, in the engineering of mass spectrometers and does exploit some modern technology in the form of digital and computer processing and a unique laser vaporization scheme for biological sample preparation, it is only one step toward what may be possible in the future. The ultimate device may be a MEMS mass spectrometer-on-a-chip. With limited prototyping and testing under way at the University of Minnesota, this project targets a 200-g, 0.5-W mass spectrometer, about the size of a penny and costing only $20. As digital technology continues to evolve, doubling in capabilities every 2 years, the signal and data processing eventually will migrate onto the chip to form a smart mass spectrometer-on-a-chip. This seems to be a natural and very promising direction for mass spectrometer sensor development. MEMS technology enables a host of other creative possibilities for detecting and recognizing biological materials. Among the miniature mechanical components that can be fabricated in MEMS are microfluidic components, such as tiny valves and pumps, which can be configured to create an integrated DNA amplifier based on the PCR process. With microvolumes (1 or 2µl) of sample material and integral on-chip heaters, the temperature cycles required by PCR for doubling the amounts of DNA each cycle can be carried out extremely rapidly—generating detectable amounts of DNA in seconds to minutes, rather than the hours that characterize conventional PCR equipment. Manipulated by microfluidics, the DNA-amplified samples can be inserted into an on-chip microfabricated capillary electrophoresis system with integrated sources and CCD detectors, for optical identification of the DNA. The result is a fast, accurate, and inexpensive DNA identification sensor. Active development of the required microfluidic MEMS technology and the DNA sensor itself is currently under way. Another MEMS-based biological sensor, currently in development in a number of laboratories, uses an array of microcantilever beams on a MEMS chip to which biological materials can be selectively attracted. Whether something attaches to a specific microcantilever can readily be detected through measurable changes in its mechanical behavior, specifically, its vibration resonance frequency. Larger matrix arrays of cantilevers can readily be fabricated and individual beams selectively coated with specific materials such as oligonucleotides by applying electrical voltages only to the selected beam or beams while flooding
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the chip with the oligonucleotide. Washing and flooding with another oligonucleotide, and a different pattern of applied voltages, can be repeated until the whole array is loaded, so to speak. When exposed to an unknown (but anticipated) nuclear material, hybridization will take place only at the beam locations prepared specifically for that material, which can be determined by surveying the mechanical properties of the individual beams in the array. Of course this is a pattern-matching sensor, not a physical-properties sensor, and as such is ineffective when confronted with an unanticipated unknown substance. In addition to MEMS, a second large class of fiber-optic-based biological and chemical sensors17 seems quite promising in its sensitivity and breath of applicability. The potential of fiber optics for all kinds of sensing,18 particularly remote sensing, was recognized in the 1960s, and the technology was applied to the measurement of the oxygen content of the blood as early as 1962.19 Typically, the material to be identified is brought into contact with the end or a portion of an optical fiber, light from a laser source is sent down the fiber, and through selective absorption or scattering of the incident light by the unknown material or through the generation of fluorescence, the unknown is identified by pattern-matching techniques based on the returned optical signals. Because of the poor detection sensitivity of absorption and scattering measurements, fluorescence is the most commonly used technique. Fluorescence can be generated directly by the sampled material in some cases or can be assisted by another fluorescent compound that selectively attaches (to tag or label) specific biological or chemical materials. One example of the latter approach is to coat the surface of the exposed core of an optical fiber with a particular antibody that remains attached to the surface of the fiber. When the fiber is exposed to various antigens, only those specific to the bound antibodies will attach. Introducing a free antibody that is fluorescently labeled and that is also specific for the targeted antigen then results in attached (antibody-antigen-labeled antibody) complexes that are detected by their characteristic fluorescence spectrum. The fiber can be prepared with multiple antibodies, which, when combined with differently tagged antibodies, gives the potential for simultaneous detection of multiple antigens. Under DARPA sponsorship, such fiber-optic biological sensors have been tested against a number of battlefield threats, such as botulism, ricin, plague, and anthrax, and they promise near-real-time (˜5 minutes) detection down to the level of 0.5 to 5.0 ng/ml. Efforts are now under way to miniaturize these sensors. In the long term, this class of sensor may also be compatible with a MEMS implementation. 17 Boisde, G., and A. Harmer. 1996. Chemical and Biochemical Sensing with Optical Fibers and Waveguides, Archtech House, Boston, Mass. 18 Giallorenzi, Thomas G., Joseph A. Bucaro, Anthony Dandridge, and James H. Cole. 1996. ''Optical-fiber Sensors Challenge the Competition," IEEE Spectrum, 23(9):44–49, September. 19 Polyani, M.I., and R.M. Hehir. 1962. "In Vivo Eximeter with Fast Dynamic Response," Rev. Sci. Instruments, 33:1050.
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Using on-chip lasers and detectors, with integrated optical waveguides in place of fibers, very small throwaway ($20) biological sensors could result. A persistent problem with all types of biological sensors is the difficulty in cleaning or resetting the sensor so that it can be used multiple times, instead of being discarded after a single use. The antibody-antigen-labeled antibody fiber-optic biosensor just described is somewhat reusable in that it can be used a second time if the first trial gives a negative result, that is, when no antigens or labeled antibodies are detected. On the other hand the dog's nose is infinitely resettable (with saturation effects and time constants, to be sure), but ultimately recyclable an unlimited number of times. There is much to learn in this discipline in the future. Other Sensors General Local Sensors Beyond the major sensor classes explicitly discussed above, there are numerous other sensors for measuring just about anything one can imagine, including temperature, humidity, position, stress, strain, speed of flow, shape, roughness, stiffness, compliance, viscosity, electrical resistivity, inductance, interatomic distances, and so on. In terms of future growth, all can be expected to benefit from the digital revolution and the significant microelectronic and digital technology trends that have been described. With few exceptions, the signal conditioning is already, or will soon become, solid state with the signal processing handled digitally. These sensors, except where constrained by the physical interface, will exploit the progress in microelectronics—digital VLSI as well as MEMS—to grow increasingly monolithic, smaller, cheaper, smarter, and distributed, with built-in microprocessor capabilities (i.e., a sensor on a chip) supporting test, calibration, communications, and sophisticated signal-processing algorithms for greatly enhanced performance. Fiber-optic Sensors Perhaps the most interesting and versatile of the general sensors are those based on fiber-optic sensor technology.20 Using the same technologies that enable the optoelectronics (e.g., CDs and laser printers) and the telecommunication industries, fiber-optic sensors are rapidly displacing a number of traditional sensors, achieving both higher performance and lower cost. Fiber-optic sensors are discussed above in the context of chemical and biological applications and their role in inertial sensing in the form of the fiber-optic gyro. But fiber-optic sensors 20 Giallorenzi, Thomas G., Joseph A. Bucaro, Anthony Dandridge, and James H. Cole. 1996. "Optical-fiber Sensors Challenge the Competition," IEEE Spectrum, 23(9):44–49, September.
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are also capable of measuring electric and magnetic fields, temperature, humidity, viscosity, stress, strain, position, acoustics, and other parameters. Any physical phenomenon that can be used to affect a light beam can provide the basis for a fiber-optic sensor. The fiber-optic sensor operates by sending a light beam through a fiber to a sensing element that, by an interaction with the physical phenomenon to be sensed, modulates some aspect of the light beam—e.g., amplitude, polarization, and frequency. The modulated return beam then propagates back through the fiber to an optical receiver and a signal/data processor where the information generated at the sensing element is extracted. Fiber-optic sensors offer a range of inherent advantages including high sensitivity, small size and weight, low power requirements, reliability, and inexpensive components. Of particular value is its ability to remotely locate the passive sensing element in hostile environments or at a significant distance from the power and processing elements because of its use of simple inert materials, its immunity to EMI, and the broadband and low-loss communication capabilities of the fiber. This ability of fiber-optic sensors to sense remotely, along with the safety aspects associated with inert materials and a lack of electrical danger, has been a key element in encouraging their current widespread use in medicine. One of the most promising new applications, where no equivalent sensors exist, is the concept of smart structures. Building on the capacity for remote operation, the concept envisions networks of fiber-optic sensors, embedded into or attached to structures as they are manufactured, to permit continuous monitoring of the status of the structure for nondestructive evaluation or real-time damage assessment or perhaps to permit control of the shape or strength of the structure via actuators. Applications to all sizes and kinds of structures are possible—structures as small as a single aircraft panel or as large as a bridge, a dam, or a whole ship. Beyond its versatility, fiber-optic sensor technology possesses an inherent compatibility with the distributed communication networks that will likely dominate future sensor systems. In the near future, fiber-optic sensors of all kinds should continue to become less expensive, displacing more and more traditional sensors and finding new applications. In the long run, they will become increasingly capable along with every other sensor and will find broad use in distributed sensor networks where mobility and wireless communications are not mandatory. Future Impact on Naval Operations Expected Evolution of Sensor Technology Based on the technology trends and historical growth patterns described, the panel anticipates that future sensor technology will be characterized by the following:
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Ever-decreasing size and cost as microelectronics evolves into nanoelectronics within the limits and constraints implied by the physics of the interfaces. Migration of the analog-to-digital conversion to the front end of the sensor, leaving only those analog elements absolutely necessary for interfacing with the physical phenomenon to be sensed—e.g., microwave LNA, filters and power amplifiers, fiber-optic transducers, MEMS transducers, and the like. Ever-increasing application of computer processing as gigaflops grow to teraflops and then to petaflops. Development of monolithic smart sensors, combining sensing transduction, ADC, digital signal processing, communication input and output, and perhaps power conditioning on a single chip. This offers interesting possibilities for very small, very smart weapons such as affordable smart bullets. Note that not all sensors can be small, even though the electronics can be. Size depends very much on the physics of the physical interface constraints. For example, propagation-based sensors such as RF radar and sonars typically require many wavelengths across the T/R aperture for good spatial resolution. Optical and millimeter-wave sensors, however, with their small wavelengths, and all MEMS-mediated sensors can and will become small and integrated. As increasingly capable sensors evolve, it will be natural to deploy collections of autonomous, mobile, communicating sensors that can cooperate to function as a single, higher-level metasensor. In a sense, the Navy's CEC already functions as a metasensor but is not yet viewed as such. In CEC, the radars are thought of as individual, independent sensors that are cooperating. The meta-interpretation views the cooperating radars as a single sensor, which happens to have distributed and mobile components. In the future, as individual sensors grow smaller and more capable, and perhaps become autonomously mobile, they will be deployed in environments where each can see only a small part of the scene and can communicate only in a limited sense with other close-by minisensors. Under these conditions it becomes natural to think of the individual sensors as members of a distributed ant-like society that, through only local communications and simple local protocols, manages to behave as a single purposeful entity—that is, a metasensor. Investigations of the dynamics and potentially chaotic behavior of such distributed systems (e.g., flocks of birds or schools of fish) have recently begun to appear in the physics literature. This direction of research should be carefully nurtured. Figure 4.11 illustrates this evolution.
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FIGURE 4.11 Sensor evolution What Will the Evolution of Sensor Technology Enable? Broadly speaking, eventually sensor technology will allow us to know everything and to hit anything. Know Everything—Situational Awareness With unlimited computational power and affordable, micro- and nanoelectronic monolithic sensor implementations in hand, the battlefield environment can be thoroughly examined by distributions of smart sensors and metasensors from multiple points of view, in multiple spectral bands, with high spatial and temporal resolution, through natural and manmade obscurations to provide a continuous awareness of the current situation. Who and what are present? Precisely where are they? Which are friends and which enemies? Are there threats present? What kind? Precisely where? What are they doing? These are the kinds of questions for which sensor information will be supplied. Hit Anything—Surgical Smart Weapons With high-resolution imaging sensors of many kinds, effective ATR and aim point selection algorithms, and large amounts of affordable and compact computational power, ever smaller and smarter weapons can be envisioned. Such inexpensive weapons, able to identify and precisely strike intended targets with high probability, can have great cost and logistic advantage. As the sensors get
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smaller and smarter, one can even imagine shrinking smart bombs to the level of smart bullets—a small bit of explosive, guided by a miniature monolithic smart sensor and controlled by means of MEMS boundary layer actuators. The panel believes that an adequate aerospace industry manufacturing infrastructure remains to produce smart weapons at a reasonable cost if the production runs are large enough. Caveats The panel sets forth the following caveats: The transition from microelectronics to nanoelectronics or to superconductor RSFQ logic implies significant reductions in operating voltages along with the threat of increasing EMI vulnerability. As the number of observing, communicating sensors on the battlefield increases, the threat of data overload also increases. At the very least, efficient and effective information-extraction procedures must be developed. Ever-increasing trends toward small, smart sensor and weapon combinations with various degrees of autonomy conjure up the possibility that the weapon will somehow turn on its masters. As autonomy is a matter of degree rather than a binary issue, confidence in the systems will evolve gradually. As mobile autonomous smart sensors and cooperating metasensors evolve, communications integrity will become an increasingly important issue. In addition, the information-networking aspects inherent in these distributed concepts suggest increasing vulnerabilities to the threat of conscious attack by means of the techniques of information warfare. Developments Needed—Military Versus Commercial The panel sees the five steps listed below as promising an overall sensor development strategy: Application of existing currently available state-of-the-art technologies. COTS products will cover much of this need, perhaps with some special packaging to make them suitable for the military environment. Basic research and development to keep the technology growth curves growing. DOD is the primary support for these critical activities. This includes such topics as wide-bandgap semiconductors, quantum wires and dots such as single-electron transistors, superconductors such as HTS, RFSQ logic, quantum computing, molecular computing, passive imaging RF/acoustics, meta-sensor community dynamics, and so forth. Realization that this technology growth does not imply that only 6.1 expenditures
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are necessary. For many technologies, superconductor RSFQ logic, RSFQ logic, for example, considerable 6.2 and 6.3 engineering developments as well as investments in manufacturing technologies are required to attain the desired economical performance levels. Attention to DOD-specific needs that must be addressed (applicable to the Department of the Navy also). This category includes such topics as digital radar, condition-based maintenance, and common-aperture electromagnetic sensor combinations, and so forth. Attention to Navy Department specific needs that must be addressed (ocean issues that will not be addressed by anyone else). This category includes such topics as littoral environments, synthetic aperture sonar, communications in the ocean, and so forth. Foreign Technology Status and Trends The technologies underlying sensors, including semiconductor and superconductor technology, digital microelectronics, computers and software, microwave, optics, and acoustic technology, and biotechnology are available worldwide. In many of these areas, the United States is not necessarily the leader, although we are not seriously deficient in any of them. Generally, the U.S. advantage lies more with the large amount of resources it is willing to invest in vigorously applying the technology to military problems, rather than with an inherent dominance of the individual technologies. Some of this is suggested by a critical technologies plan21 crafted by the DOD in 1990, when the Soviet Union was still thought to be the prime threat. Table 4.3 is a summary assessment of foreign technical capabilities vis-à-vis those of the United States adapted from the DOD report. Interestingly enough, this study concluded that in the all-important area of microelectronics, Japan led the United States in all areas except radiation-hardened electronics, for which there is only a limited commercial market, principally satellite and nuclear power plants. Japan also excelled in photonics, superconductivity, and biotechnology, with considerable strength in machine intelligence and robotics, which are particularly relevant to the development of metasensors. The manufacturing of microelectronics has now spread throughout Southeast Asia. And China, with its vast human resources and unquestionably competent scientists and engineers, is rapidly coming up to speed. The 1990 DOD report also suggested that although North Atlantic Treaty Organization (NATO) allies were lagging at that time in most microelectronic technologies, this situation could change drastically in the near term if the capabilities of individual European countries were integrated. 21 Department of Defense. 1990. Critical Technologies, Department of Defense, Washington, D.C., March 15.
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TABLE 4.3 Summary of Foreign Technical Capabilities Critical Technologies USSR NATO Alliens Japan Semiconductor materials and microelectronic circuits ◆ ◇◇ ◇◇◇◇ Software producibility ◆ ◇◇ ◇◇ Parallel computer architectures ◆ ◇◇ ◇◇ Machine intelligence and robotics ◆ ◇◇◇ ◇◇◇◇ Simulation and modeling ◆ ◇◇◇ ◇◇◇ Photonics ◆◆ ◇◇ ◇◇◇◇ Sensitive radar ◆ ◇◇ ◇◇ Passive sensors ◆◆ ◇◇ ◇◇ Signal processing ◆◆ ◇◇ ◇◇ Signature control ◆◆ ◇◇ ◇◇ Weapon system environment ◆◆◆ ◇◇◇ ◇◇ Data fusion ◆◆ ◇◇ ◇◇ Computational fluid dynamics ◆ ◇◇ ◇◇ Air-breathing propulsion ◆◆ ◇◇◇ ◇◇ Pulsed power ◆◆◆◆ ◇◇ ◇◇ Hypervelocity projectiles ◆◆◆ ◇◇ ◇◇ High-energy-density material ◆◆◆ ◇◇◇ ◇◇◇ Composite materials ◆◆ ◇◇◇ ◇◇◇ Superconductivity ◆◆ ◇◇ ◇◇◇◇ Biotechnology materials and processes ◆◆ ◇◇◇ ◇◇◇◇ Position of USSR relative to the United States Capabilities of others to contribute to the technology ◆◆◆◆ Significant leads in some niches of technology ◇◇◇◇ Significantly ahead in some niches of technology ◆◆◆ Generally on a par with the United States ◇◇◇ Capable of making major contributions ◆◆ Generally lagging except in some areas ◇◇ Capable of making some contributions ◆ Lagging in all important aspects ◇ Unlikely to make any immediate contribution SOURCE: Adapted from Department of Defense, 1990, Critical Technologies, Department of Defense, Washington, D.C., March 15. That other nations excel in various sensor areas is well known. In fact, the Navy is currently deploying a shipboard infrared video ◡ system made by the French rather than a U.S. version. In another sensor application, it is known that the former Soviet Union has already deployed dual-band optical missile seekers with antijam performance superior to that of U.S. systems. In other words, just about everybody has the requisite technology to compete in sensor technology. The race will go to the diligent.
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Time Scale for Development and Deployment In a general way, the time scale has been addressed through the identification of the exponential growth characteristics of various technology components and their projected performance capabilities as a function of time out to 2035. Over the next four decades, sensors will continue to evolve, and advances can be expected to be deployed within about 5 years of the time of the projected state-of-the-art capability. Note that all of the technology growth curves presented are conservative, in that they represent affordable, obtainable capabilities, representative of the near state of the art—not the best, one-of-a-kind achievements. For example, the clock speed of microprocessors in desktop personal computers is indicated as 200 MHz today, which is available as a COTS Pentium or Cyrix 6 × 86 from multiple suppliers. Processors with speeds exceeding this have been demonstrated already, with the best performance currently reaching the 400- to 600-MHz range. With this in mind, desktop computers with clock speeds of 1 GHz are expected to be commercially available by about 2005, and military applications of 1-GHz computers might reach the field over the next 5 years from 2005 to 2010. Recomendation Naval operations are increasingly dependent on enhanced sensor data to provide situational awareness, target designation, weapon guidance, condition-based maintenance, platform automation, personnel health and safety monitoring, and logistic management. The Department of the Navy should provide continuing support of sensor technology for areas critical to future naval operations. Special attention should be given to applications of microelectromechanical systems technology because it offers the advantage of low-cost, high-capability systems-on-a-chip that will enable future cooperative sensor networks.
Representative terms from entire chapter: