Principles of Modern Radar - Volume 2 1891121537

670 CHAPTER 15 Multitarget, Multisensor Tracking• Tracking performance suffers when the track filter predictions fail to match the truetarget dynamics. The IMM estimator and VS-IMM estimator are recommended foraddressing target sets with multiple possible modes of target dynamics.• Multisensor tracking (or sensor fusion) is increasingly common for four primary reasons:necessity, observability, capacity, and robustness.• Multisensor tracking is not a panacea. It shows great potential, but if executed poorly,it can actually degrade single-sensor tracking performance.NotationThe following lists many of the variable names from this chapter:x = state vectorP = covariance matrixλ = eigenvalue of the covariance matrixθ = orientation angle of the covariance ellipsec (i, j) = cost of associating track i and measurement jc I = cost of initiating a new track in measurement-to-track data associationG = guard value, or cost of coasting a track in measurement-to-track data association ij = log-likelihood between track i and measurement j˜z ij = innovations, or the difference between the propagated state of tracki (after a measurement conversion) and the state of measurement jS ij = innovations covariance between track i and measurement jz j = state of measurement jR j = covariance of measurement jH ij = measurement matrix, or the Jacobian of the coordinate conversion from the trackstate space to the measurement state space, linearized around the track stateM ij = Mahalanobis distance between track i and measurement jF = propagation matrix in the Kalman FilterK = Kalman gainR 0 j = SNR of measurement jR i = Average SNR of track iR th = SNR detection thresholdμ l is the probability of mode l in the IMM estimatorμ l,m = probability of having been in mode l at t k−1 given that mode m is the best at t kp(l,m) = probability of switching from mode l to mode m¯c m = probability of being in mode mAcronymsCEC cooperative engagement capabilityCRLB Cramer-Rao lower boundEKF extended Kalman filterGMTI ground moving target indicatorHOMHT hypothesis oriented multiple hypothesis trackerIMM interacting multiple model estimatorJVC Jonker-Volgenant-Castanon auction algorithmLLR log-likelihood ratioMHT multiple hypothesis tracker