Objective functions for bayesian control-theoretic sensor management, 1: multitarget first-moment approximation
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[1] R. Mahler. A Theoretical Foundation for the Stein-Winter "Probability Hypothesis Density (PHD)" Multitarget Tracking Approach , 2000 .
[2] A. Jazwinski. Stochastic Processes and Filtering Theory , 1970 .
[3] Y. Ho,et al. A Bayesian approach to problems in stochastic estimation and control , 1964 .
[4] I. R. Goodman,et al. Mathematics of Data Fusion , 1997 .
[5] Ronald P. S. Mahler,et al. Random Set Theory for Target Tracking and Identification , 2001 .
[6] Ronald P. S. Mahler,et al. Multisensor-multitarget sensor management: a unified Bayesian approach , 2003, SPIE Defense + Commercial Sensing.
[7] Keith D. Kastella,et al. Practical implementation of joint multitarget probabilities , 1998, Defense, Security, and Sensing.
[8] Ronald Mahler,et al. Multitarget Moments and their Application to Multitarget Tracking , 2001 .
[9] Ronald Mahler,et al. Bulk multitarget tracking using a first-order multitarget moment filter , 2002, SPIE Defense + Commercial Sensing.
[10] R. Mahler. Engineering statistics for multi-object tracking , 2001, Proceedings 2001 IEEE Workshop on Multi-Object Tracking.
[11] M. Kouritzin,et al. A Branching Particle-based Nonlinear Filter for Multi-target Tracking , 2001 .
[12] Ronald P. S. Mahler,et al. Extended first-order Bayes filter for force aggregation , 2002, SPIE Defense + Commercial Sensing.
[13] Ronald P. S. Mahler,et al. Multitarget Markov motion models , 1999, Defense, Security, and Sensing.
[14] Ronald P. S. Mahler,et al. Global posterior densities for sensor management , 1998, Defense, Security, and Sensing.