Communications: directive radio wave systems and devices (e.g. – Directive – Beacon or receiver
Reexamination Certificate
1999-09-14
2001-09-18
Issing, Gregory C. (Department: 3662)
Communications: directive radio wave systems and devices (e.g.,
Directive
Beacon or receiver
C342S090000, C342S162000
Reexamination Certificate
active
06292136
ABSTRACT:
TECHNICAL FIELD OF THE INVENTION
The present invention relates in general to tracking of multiple targets by means of measurements from various sensors and in particular to track initiation during multiple target tracking by means of measurements from passive sensors.
PRIOR ART
Traditionally, tracking has been performed using measurements from active sensors, such as radar's or active sonar's, which report measurements from different sources. These sources may be targets of interest as well as noise or false targets. Tracking serves the object to organise the sensor data into sets of observations, hereinafter denoted tracks, produced by the same source. Once the existence of a track has been established it is possible to estimate related quantities, such as the target position, velocity, acceleration as well as other specific characteristics.
The basics of multiple target tracking include three phases; track initiation, track maintenance and track deletion. Track initiation involves processes in which a set of single measurements are collected and a likelihood that they originate from the same source is calculated. When such a probability is high enough, a track is created and associated with a probable target. Track maintenance comprises calculations of track or target characteristics, but may also be used to predict the behaviour of the target in a near future. Such estimates are often computed by filtering of a series of similar measurements over a certain time period, since the individual measurements often contain measurement errors and noise. These calculations normally involve previous measurements, condensed into the so called states of the track, or predictions as well as new measurements from the sensors. This means that once a track is created, it “consumes” new measurements, which fall close enough to the predicted characteristics of the target, and such measurements are not used to initiate new tracks.
Even if a target disappears, or at least avoids being detected, the track will survive for a certain time, in order to handle missed detection's or shorter malfunctions. However, the estimates of the track characteristics deteriorate, and so do the predictions. When the estimates and predictions become too uncertain, the track is no longer of use, and should be deleted. Such track deletion may be based on calculated uncertainty levels of the estimated track parameters or on a certain numbers of “missing” observations.
The tracking step incorporates the relevant measurements into the updated track parameter estimates. Predictions are made to the time when the next data set is to be received. This prediction constitutes the origin from which the determination of whether a new measurement fits into the track or not is made. The selection of new measurements as belonging to the track or not is known as “gating” or measurement association. The prediction typically constitutes the middle of the gate, and if the measurement falls within a certain gate width, it will for example be assumed to belong to the track. A common way to perform estimation and prediction is by employing Kalman filtering. Further references to Kalman filtering can be found in “Estimation and Tracking: Principles, Techniques, and Software” by Bar-Shalom and Li, Artech House, USA, 1993, page 209 to 221.
A description of tracking systems of prior art can e.g. be found in “Multiple-Target Tracking with Radar Applications” by Samuel S. Blackman, Artech House, USA, 1986, page 4 to 11.
In prior art multi target systems, radar is often used. Radar measurements provide information about azimuth angle and range (2D radar's), and in most cases even the elevation (3D radar's), with respect of the sensor position. It will be understood that from such measurements, estimates of target positions, velocities etc. are easily obtainable within the above described scheme.
In modern tracking systems, especially in military applications, the use of radar measurements is not solely of benefit. Since the radar is an active sensor, it radiates energy and records reflected waves, from which the position can be determined. However, such radiating sources are easily located by enemies and may therefore be destroyed by missiles or assist in the navigation of an hostile target. It is therefore advantageous if tracking would be possible to perform using only passive sensors, such as jam strobes from the targets, ESM (Electronic Support Measures) sensors or IR-/EO-sensors (infrared/ElectroOptical). A major disadvantage with the passive sensors as compared with radar is that they do not have any possibility to detect any range information from a single sensor. They will normally only provide measurements of the azimuth (1D sensor) or azimuth and elevation (2D sensor), with respect of the sensor location.
An obvious approach to overcome such a problem is to employ at least two sensors, separated by a distance, and use the combination of the measurements. By this it is possible to perform a geometrical triangulation, which at least in principle may give the absolute positions of the target as the intersection point between two measurement directions. The measurement directions are hereinafter referred to as “strobes”, and the intersections are denoted as “crosses”. However, if there are several targets present in the area at the same time, pure geometrical considerations are not enough to find the unique target positions, since there generally are more crosses between strobes than true targets. A cross that does not correspond to any true target is denoted a “ghost”. Furthermore, since the measurements are corrupted by errors, strobes including both azimuth and elevation may not even intersect each other exactly. Thus, there is a need for a process in which the true targets among the crosses are identified and in which the ghosts are rejected.
A possible way to solve this problem is to calculate all possible crosses from all possible strobes and formulate a maximum likelihood problem. Such a problem may be solved in a conventional way by computers, but using a number of sensors tracking a number of targets will produce very large number of crosses. The computer time which is needed for such calculations will grow tremendously with the number of targets and the number of sensors, and even for relatively moderate numbers, the calculations will be impossible to perform on computers of today in real time. It is obvious for someone skilled in the art that a tracking system that cannot perform in real time is of no use.
In the U.S. Pat. No. 4,806,936 a method of determining the positions of multiple targets using bearing-only sensors only is disclosed. In this method, individual strobe measurements from three sensors are used. The intersecting bearing lines form triangles representing both true targets and ghosts. The separation of the ghosts from the true targets is performed by analysing the size and position of each triangle and in gating processes eliminate some of the ghosts. The remaining set of triangles is entered into a maximum likelihood procedure to extract the true targets. The gating process is based on simple geometrical measures, such as the difference between the individual strobes and the geometrical centre of gravity of the triangles. Such measures are however sensitive to measurement uncertainties since an uncertain measurement will enter the calculations with the same computational weight as the more accurate ones. Since the individual strobes, which normally involve large measurement uncertainties, are used for these calculations, the determinations of position of the true targets can not be performed very accurately. Furthermore, the assumption that there must exist a detection from three individual sensors will limit the range of detection significantly. It is also not obvious how to make a generalisation to more than three sensors. An obvious disadvantage with the above method is also that all the sensors have to be synchronised in order to allow a comparison between the individual strobes.
Issing Gregory C.
SAAB AB
Young & Thompson
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