Reprint

Innovative Target Tracking Techniques for Modern Radar and Sonar Systems

Edited by
January 2023
350 pages
  • ISBN978-3-0365-3537-1 (Hardback)
  • ISBN978-3-0365-3538-8 (PDF)

This book is a reprint of the Special Issue Innovative Target Tracking Techniques for Modern Radar and Sonar Systems that was published in

Chemistry & Materials Science
Engineering
Environmental & Earth Sciences
Summary

The aim of this Special Issue is to gather recent advances and development in target tracking techniques to determine how they can be adapted for modern radar and sonar systems. After peer review, 17 articles in related areas have been accepted for publishing in this Special Issue. The published articles cover a range of topics and applications central to target tracking. There are eight papers about general multi-target tracking, including the topics of joint tracking and classification [3], adaptive estimation using clutter measurement probability [6], joint localization and tracking [7], extended target tracking [8], tracking with smoothing [11], DOA tracking [12], tracking under low detection probability [14], and sonar tracking and interception [17]. Three papers address multi-sensor multi-target tracking methods. Specifically, a multi-target estimating method for pulsed radar systems is proposed in [2], a joint dwell time and bandwidth optimization method in a radar network is proposed in [4], a and multiple marine ship tracking method with unknown backgrounds is presented in [9]. There are 2 papers [10,15] on the problem of target assignment in multi-sensor multi-target tracking. Moreover, Mallick et al. considered measures of nonlinearity of a polynomial curve in two dimensions [1], Zhao et al. explored the use of calibration targets for which the positions are known to the MPR system, to counter the loss in target localization accuracy arising from transmitter/receiver position errors [13], and Li et al. proposed an algorithm to apply the frequency diversity technique to passive azimuth estimation in [16].

Format
  • Hardback
License
© 2022 by the authors; CC BY-NC-ND license
Keywords
direction of arrival estimation; frequency diversity; passive sonar; Doppler data association (DDA); Doppler measurement; kinematic state estimation; multi-target tracking; tracking performance; refined PHD filter; low detection probability; continuous miss detection; radar multi-target tracking; survival probability; target labels; posterior weight revision; sequential probability ratio test; hypothesis test; multi-static passive radar; target localization; calibration target; bistatic range; transmitter and receiver position error; Cramér–Rao lower bound; direction-of-arrival (DOA) tracking; impulse noise; Multi-Bernoulli filter; particle filtering; labeled RFS; RTS smoother; GLMB filter; target handover; seamless multi-target tracking; radar network systems; optimal scheduling; situational awareness; random finite sets; unknown background; bootstrapping method; GLMB filter; multisensor multitarget tracking; Murty’s algorithm; extended target; target tracking; PHD filter; high clutter density; passive localization; time difference of arrival; angle of arrival; random finite sets; Gibbs sampling; GLMB filter; multi-target tracking; data association; clutter measurement density; spatial clutter measurement density estimator; multi-target tracking; target motion analysis; bottom bounce path; ray tracing; particle swarm optimization; low probability of intercept (LPI); Bayesian Cramer–Rao lower bound (BCRLB); multi-target tracking; radar network; joint tracking and classification; scattering center model; high range resolution profile; CBMeMBer filter; sequential Monte Carlo; linear frequency modulation; pulse compression; matched filter; Doppler shift compensation; Pulse-Doppler radar; moving target indication; comb filter; clutter suppression; biosonar; predictive tracking; tracking algorithms; polynomial curve in 2D; measures of nonlinearity (MoNs); extrinsic curvature; Beale’s MoN; Linssen’s MoN; Bates and Watts parameter-effects curvature; direct parameter-effects curvature; Li’s MoN; MoN of Straka, Duník, and S̆imandl; maximum likelihood estimator (MLE); Cramér-Rao lower bound (CRLB)