A PDF multitarget tracker

A probability density function (pdf) based approach to the multitarget tracking problem is presented. The input data are obtained by measurements over time from a front-end detector. The desired output is the number of targets present and the parameters of each target. The same approach has previously been used for time delay detection and tracking problems and is adapted to this problem This approach is an alternative to the traditional approach of “association” and “tracking” on the measurements     

Rate-aided multisignal time delay detection and tracking

Time delay detection and tracking problems have been investigated in previous papers. The approach used is applicable to many problems. In those papers, a first-order Markov process was assumed for the signal parameter (time delay) dynamic model and a constant signal parameter value was assumed within a “block”, or processing unit of time. A performance degradation is incurred when the signal parameter value is “nearly constant-rate”. Also, “crossing” signal parameter values from different signals cannot be tracked. The detector-trackers will “switch” signals. To combat these difficulties, the signal parameter dynamic model is assumed to be a second-order Markov process, and signal parameter rate of change information is computed within a block. A rate-aided multisignal detection and tracking system is developed with these assumptions     

An Optimum First-Order Time Delay Tracker

The key to the general estimation problem is the computation ofthe posterior probability density function (PDF) of the desiredparameter, or PDF conditioned on knowing all availableobservations. Any optimum estimate can be computed from this PDF. The theory and implementation of a numerical solution ispresented for the computation of the posterior PDF in real time fortime delay tracking with a first-order Markov assumption. Benefitsinclude a lack of threshold effects usually associated with nonlineartrackers as well as theoretically optimum performance.     

Multisignal time delay detection and tracking

An optimum solution to the time delay detection and tracking problem for a single signal is extended to the multisignal problem where the number of signals present in the observed data (if any) is unknown. The number of signals present is determined, and the time delay of each detected signal is tracked. The number of possible global, or first level, hypotheses is large because of the exponential dependence on the number of potential signals. An efficient approximate multisignal detection and tracking solution that is as near optimum as possible for the computational resources required is developed. It has the form of parallel detector-trackers (one for each potential signal) each similar to the single-signal case, with communication between them. Test results demonstrate the utility of the approach     

Optimum time delay detection and tracking

An optimum solution to the time delay tracking problems has been previously achieved by recursively computing the time-delay posterior probability density function (PDF), or time-delay PDF conditioned on knowing all observed data, by numerical means. Any optimum estimate is determined from the posterior PDF. The same approach is extended to an optimum solution for the time delay detection problem with a randomly appearing and disappearing signal. The detector-tracker is suitable for a stand-alone detection and tracking system