MCMC methods for tracking two closely spaced targets using monopulse radar channel signals

Abstract

This paper discusses four techniques to successfully track two closely-spaced and unresolved targets using monopulse radar measurements, the quality of such tracking being a determinant of successful detection of target spawn. It explores statistical estimation techniques based on the maximum likelihood criterion and Gibbs sampling, and addresses concerns about the accuracy of the measurements delivered thereby. In particular, the Gibbs approach can deliver joint measurements (and the associated covariances) from both targets, and it is therefore natural to consider a joint filter. The ideas are compared; and amongst the various strategies discussed, a particle filter that operates directly on the monopulse measurements seems to be best.

A modified MCMC approach for classifying target and decoy

“…We take in-phase components as example (the quadrature components are similar), defined as: Under the Equation (1), Isaac et.al [11] developed a Gibbs sampler to estimate the location of the objects in two unre solved objects tracking scenario. Since the power spectrum densities of target and decoy are always unkown in decoy jamming scenario, Gibbs sampler is intractable to be directly used in classifying the target and decoy.…”

“…Thus, these approaches cannot be adopted in decoy jamming scenario. Fortunately, in recent years, Markov chain Monte Carlo (MCMC) has been widely used in object tracking and target recognition [11][l3] [14]. Dealing with high-dimensional problems, to our best knowl edge, MCMC is a general approach for providing a solution within a reasonable time [ 15].…”

“…The motivation of this paper benefits from the most success of MCMC in [11]. In [11], Gibbs algorithm of MCMC has been put forward to solve the tracking problem of unresolved objects.…”

“…In [11], Gibbs algorithm of MCMC has been put forward to solve the tracking problem of unresolved objects. Since the Gibbs algorithm requires full condition distributions of the unknown parameters, it cannot be utilized directly in decoy jamming scenario.…”

A Joint Detection and Tracking Algorithm for Unresolved Target and Radar Decoy

“…Particle filtering techniques that have the advantage of providing computational tractability are applicable under most general circumstances since there is no assumption made on the form of the density. Some methods utilizing particle filter were introduced to detect and track two closely spaced targets [44,45], and they focused on constructing hypothesis testing for detection based on Akaike information criterion (AIC) and using particles to achieve state estimation [46,47].…”