IMMPDAF for radar management and tracking benchmark with ECM

A framework is presented for controlling a phased array radar for tracking highly maneuvering targets in the presence of false alarms (FAs) and electronic countermeasures (ECMs). Algorithms are presented for track formation and maintenance; adaptive selection of target revisit interval, waveform and detection threshold; and neutralizing techniques for ECM, namely, against a standoff jammer (SOJ) and range gate pull off (RGPO). The interacting multiple model (IMM) estimator in combination with the probabilistic data association (PDA) technique is used for tracking. A constant false alarm rate (CFAR) approach is used to adaptively select the detection threshold and radar waveform, countering the effect of jammer-induced false measurements. The revisit interval is selected adaptively, based on the predicted angular innovation standard deviations. This tracker/radar-resource-allocator provides a complete solution to the benchmark problem for target tracking and radar control. Simulation results show an average sampling interval of about 2.5 s while maintaining a track loss less than the maximum allowed 4%.

[1]  Yaakov Bar-Shalom,et al.  Design of an interacting multiple model algorithm for air traffic control tracking , 1993, IEEE Trans. Control. Syst. Technol..

[2]  Yaakov Bar-Shalom,et al.  Estimation and Tracking: Principles, Techniques, and Software , 1993 .

[3]  W. Dale Blair,et al.  Interacting multiple model algorithm for solution to benchmark problem for tracking maneuvering targets , 1994, Defense, Security, and Sensing.

[4]  G. L. Gentry,et al.  Benchmark problem for beam pointing control of phased array radar against maneuvering targets in the presence of ECM and false alarms , 1995, Proceedings of 1995 American Control Conference - ACC'95.

[5]  Samuel S. Blackman,et al.  Application of multiple-hypothesis tracking to agile beam radar tracking , 1996, Defense, Security, and Sensing.

[6]  T. Kirubarajan,et al.  Adaptive beam pointing control of a phased array radar in the presence of ECM and false alarms using IMMPDAF , 1995, Proceedings of 1995 American Control Conference - ACC'95.

[7]  Yaakov Bar-Shalom,et al.  Tracking with debiased consistent converted measurements versus EKF , 1993 .

[8]  Krishna R. Pattipati,et al.  IMM estimation for multitarget-multisensor air traffic surveillance , 1997 .

[9]  Edward W. Kamen,et al.  Tracking a maneuvering target using jump filters , 1994, Proceedings of 1994 American Control Conference - ACC '94.

[10]  Samuel S. Blackman,et al.  IMM/MHT tracking and data association for benchmark tracking problem , 1995, Proceedings of 1995 American Control Conference - ACC'95.

[11]  Bruno O. Shubert,et al.  Random variables and stochastic processes , 1979 .

[12]  Yaakov Bar-Shalom,et al.  Interacting multiple model tracking with target amplitude feature , 1993 .

[13]  Yaakov Bar-Shalom,et al.  Benchmark for radar allocation and tracking in ECM , 1998 .

[14]  F. Daum,et al.  "Multitarget-Musitisensor Tracking; Principles and Techniques" [Book Review] , 1996, IEEE Aerospace and Electronic Systems Magazine.

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

[16]  William Dale Blair,et al.  Benchmark problem for beam pointing control of phased array radar against maneuvering targets , 1994, Proceedings of 1994 American Control Conference - ACC '94.

[17]  Y. Bar-Shalom,et al.  Adaptive beam pointing control of a phased array radar using an IMM estimator , 1994, Proceedings of 1994 American Control Conference - ACC '94.

[18]  Krishna R. Pattipati,et al.  Comparison of IMMPDA and IMM-assignment algorithms on real air traffic surveillance data , 1996, Defense, Security, and Sensing.