Communications: directive radio wave systems and devices (e.g. – Determining distance – Triangulation
Reexamination Certificate
2002-07-22
2004-02-10
Lobo, Ian J. (Department: 3662)
Communications: directive radio wave systems and devices (e.g.,
Determining distance
Triangulation
C342S444000, C342S463000, C342S465000, C367S124000
Reexamination Certificate
active
06690321
ABSTRACT:
FIELD OF INVENTION
This invention relates to passive sensing, and more particularly, to a system that can detect the presence of, and bearing to multiple targets that pass between sensor pairs in an array of sensors positioned to intercept emissions from the targets.
BACKGROUND OF THE INVENTION
The last decade of the twentieth century has marked a significant shift in the roles and requirements for today's soldier and small unit team. The “spectrum of conflict” is fast encompassing not only the basic objectives of homeland defense and protection of vital national interests but also peacekeeping and Operations Other Than War.
Lighter, more dispersed, forces are now required to confront situations where the response to any military action may be uncertain, confused, and with potentially rapid transitions to combat. These types of missions place a premium on the ability of small-dispersed forces to rapidly assess their tactical situation without the ability or time to call upon larger surveillance assets.
Key to this ability is faster and more local access to information to support diverse and rapidly changing situations encountered during these missions. Increasingly, forces are called on to participate in activities in areas where little previous information has been gathered on the terrain, where the potential exists for conflict with non-traditional combatants using non-traditional tactics, and in areas not well supported by existing intelligence systems.
Today's soldier can be involved in refugee care at one moment and confronted with full-scale combat in the next. Often these changing situations occur within the same small geographic area such as towns or villages, or street-to-street. These new situations require the ability to access timely local intelligence. The war of the future will be a sensor war; and control of sensor placement and sensor outputs will be key.
Technology is now available to aid in surveillance of the battle space at a cost that makes it affordable for individual soldiers and small units to use. Low cost, easily deployed, micro airborne, ground, and littoral sensor networks are the key to providing the type of information needed by these small soldier teams.
Low cost soldier-controlled sensing devices can extend a small unit's area of influence by providing on-demand local gap-filling situation awareness for missions ranging from reconnaissance to targeting of precision-guided munitions. These sensors give the soldier the immediate ability to see “what's over the next hill” and “what's around the next corner,” which the information that can make the difference between failure and success.
These 'sensor networks encompass a variety of sensor types, deployment modes, endurance, and capability. Sensor detection ranges vary from kilometers for air and ground vehicles to meters for personnel and parked ground vehicles. Distributed sensor networks with large numbers of nodes provide more opportunities to follow targets, with greater likelihood that some set of sensors will be optimally placed for classification and verification.
However, distributed sensor networks pose new challenges in the design of algorithms for processing the sensor signals into useful information. Raw data that is initially distributed among many sensor nodes must be combined to generate the desired information. However, the use of interconnecting radio frequency links must be minimized to avoid detection and jamming as well as to conserve power. Power consumption is critical to surveillance lifetime as well as packaging and deployment techniques.
Collaborative processing approaches that build on local collaboration between sensors are attractive because they restrict most communications to nearby sensors, minimizing communication energy requirements.
Collaborative Signal Processing involves low-level sensor processing which occurs local to a sensor node, the exchange of data among sensor nodes to enable decision and other high-level data to be derived from raw sensor signals, a process in which a consensus is reached among sensor nodes about what is occurring in the physical world and reports or digests are created for transmission to users, and the minimization of power consumption one sensor nodes, including communications, signal processing, and sensors.
In the past, arrays of passive listening devices have been used to track tanks and other vehicles. However, at acoustic frequencies the beam widths are too broad to be able to detect individual acoustic targets, which precludes being able to count them. As a result, while vehicle noise can indicate the presence of a vehicle, the number of vehicles is often times difficult to ascertain. Thus the size of an enemy force is difficult to predict.
If techniques are used to distinguish vehicle-generated sounds based on amplitude, these systems are easily spoofed or counter measured. Also, acoustic targets that are close to the sensor inherently have higher amplitude signals than those far way. So amplitude alone is a poor indication of the number of vehicles in a surveilled area.
In order to be able to recognize separate acoustic targets, there have been efforts to triangulate on the targets from an array of sensors which are to establish bearing lines to the acoustic source. However, the beam width of acoustic listening devices is on the order of 12°, which, depending on distance to the acoustic source and the size of the source can result in detecting multiple targets as one target.
Moreover, if triangulation is used to locate the acoustic sources, the area of uncertainty in the position of multiple bearing line overlap is usually quite large. This can mask the presence of multiple acoustic sources.
Secondly, there are so called ghost bearing line crossovers that give false indications of an acoustic source where no acoustic source exists. This means that more acoustic sources will be detected than actually exist.
Thirdly, triangulation type systems are not easily scalable because of the intense computational load when performing many triangulation calculations.
Thus systems that depend on triangulation to ascertain the number and position of multiple acoustic sources are inaccurate and require considerable computer resources. This in turn translates into massive power consumption. Since most of the sensors are battery-powered, triangulation type systems have only limited life due to the limited power available from batteries.
SUMMARY OF THE INVENTION
In order to solve the problems associated with triangulation type systems, a computationally simpler system utilizes a technique in which bearings from pairs of sensors are subtracted one from the other to provide a bearing difference value, or “delta.” This value is 180° if the target is on a line between the two sensors, and rapidly drops off as the target moves to either side of this line. A target is said to be detected when this difference value is greater than for instance 150°. This means that the target is relatively close to the line between the sensors.
Bearing is determined locally and does not involve triangulation with its computationally intense algorithms. Also, the two sensors of a pair may be in communication such that a target alarm is only transmitted when the target is sufficiently close to the line between the sensors.
This means that as to the sensor pair, distant targets are ignored all together since the “delta” between bearing lines approaches 0°.
Moreover, targets that are in the vicinity but are too far from the line between the sensors are ignored, again because their “delta” is below a threshold that indicates that the target is somewhere between the sensors close to the line between them.
By processing as targets only those acoustic sources which have a bearing difference value above a preset “delta” threshold, not only do the number of targets indicated reflects the correct number, less communication and computer processing is required.
Of course if the multiple targets all exist in the beam pattern of the sensors in a pair, t
Bae Systems Information and Electronic Systems Integration Inc.
Lobo Ian J.
Long Daniel J.
Tendler Robert K.
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