Multisensor target-tracking performance with bias compensation

In this paper, multisensor-multitarget tracking performance with bias estimation and compensation is investigated when only moving targets of opportunity are available. First, we discuss the tracking performance improvement with bias estimation and compensation for synchronous biased sensors, and then a novel bias estimation method is proposed for asynchronous sensors with time-varying biases. The performance analysis and simulations show that asynchronous sensors have a slightly degraded performance compared to the "equivalent" synchronous ones. The bias estimates as well as the corresponding Cramer-Rao Lower Bound (CRLB) on the covariance of the bias estimates, i.e., the quantification of the available information on the sensor biases in any scenario are also given. Tracking performance evaluations with different sources of biases --- offset biases, scale biases and sensor location uncertainties, are also presented and we show that tracking performance is significantly improved with bias estimation and compensation compared with the target tracking using the original biased measurements. The performance is also close to the lower bound obtained in the absence of biases.

[1]  Thia Kirubarajan,et al.  Estimation with Applications to Tracking and Navigation: Theory, Algorithms and Software , 2001 .

[2]  T. Kirubarajan,et al.  Performance Limits of Track-to-Track Fusion vs . Centralized Estimation : Theory and Application , 2001 .

[3]  Lawrence D. Stone,et al.  Track-to-track association and bias removal , 2002, SPIE Defense + Commercial Sensing.

[4]  Neil J. Gordon,et al.  Performance bounds for recursive sensor registration , 2003, Sixth International Conference of Information Fusion, 2003. Proceedings of the.

[5]  Y. Bar-Shalom,et al.  Low observable target motion analysis using amplitude information , 1995, Proceedings of 1995 American Control Conference - ACC'95.

[6]  Ali T. Alouani,et al.  Tracking with three asynchronous sensors: solution existence and performance analysis , 2002, SPIE Defense + Commercial Sensing.

[7]  T. Zadra,et al.  Precision tracking of ground targets , 2000, 2000 IEEE Aerospace Conference. Proceedings (Cat. No.00TH8484).

[8]  Y. Bar-Shalom,et al.  Exact multisensor dynamic bias estimation with local tracks , 2004, IEEE Transactions on Aerospace and Electronic Systems.

[9]  B. Friedland.  Treatment of bias in recursive filtering , 1969 .

[10]  R. Bishop,et al.  Solution to a multisensor tracking problem with sensor registration errors , 1999 .

[11]  Henk A. P. Blom,et al.  Systematic error estimation in multisensor fusion systems , 1993, Defense, Security, and Sensing.

[12]  T. Kirubarajan,et al.  Multisensor multitarget bias estimation for general asynchronous sensors , 2005, IEEE Transactions on Aerospace and Electronic Systems.

[13]  T. R. Rice,et al.  A Two-Stage Filter for State Estimation in the Presence of Dynamical Stochastic Bias , 1992, 1992 American Control Conference.

[14]  Yakov Bar-Shalom,et al.  Multitarget-Multisensor Tracking: Principles and Techniques , 1995 .

[15]  Ali T. Alouani,et al.  Sensor registration in multisensor systems , 1992, Defense, Security, and Sensing.

[16]  Thiagalingam Kirubarajan,et al.  Multisensor-multitarget bias estimation of asynchronous sensors , 2004, SPIE Defense + Commercial Sensing.

[17]  K. Kastella,et al.  Bias modeling and estimation for GMTI applications , 2000, Proceedings of the Third International Conference on Information Fusion.

[18]  B. Ristic,et al.  Maximum likelihood registration for multiple dissimilar sensors , 2003 .

[19]  Y. Bar-Shalom.  Mobile radar bias estimation using unknown location targets , 2000, Proceedings of the Third International Conference on Information Fusion.

[20]  M. Ignagni,et al.  Separate bias Kalman estimator with bias state noise , 1990 .

[21]  Yaakov Bar-Shalom.  Airborne GMTI radar position bias estimation using static-rotator targets of opportunity , 2001 .

[22]  M. Ignagni.  An alternate derivation and extension of Friendland's two-stage Kalman estimator , 1981 .

[23]  S. Mori.  Tracking performance evaluation: track accuracy in dense target environments , 1990, Defense + Commercial Sensing.

[24]  Thiagalingam Kirubarajan,et al.  Multisensor bias estimation using local tracks without a priori association , 2003, SPIE Optics + Photonics.

[25]  A.S. Hauksdottir,et al.  Integrity monitoring and estimation of systematic errors in radar data systems , 1995, Proceedings International Radar Conference.

[26]  T. R. Rice,et al.  Removal of alignment errors in an integrated system of two 3-D sensors , 1993 .

[27]  Y. Bar-Shalom,et al.  Unbiased converted measurements for tracking , 1998 .

[28]  Richard J. Kenefic.  Local and remote track file registration using minimum description length , 1993 .