An improved single-point track initiation using GMTI measurements

A ground moving target indicator (GMTI) radar measures range, azimuth, and Doppler or range-rate of a target. The range-rate measurement, which is the key measurement of a GMTI radar, is used to differentiate a ground moving target from clutter when the radial velocity of the target exceeds the minimum detectable velocity (MDV). The range and azimuth measurements provide an accurate estimate of the target position. A number of track initiation algorithms using GMTI measurements are known at present. All track initiation algorithms set the initial velocity to zero and a large prior covariance for velocity is used based on the maximum target speed. The range-rate measurement is then used to update the target velocity or state. The range-rate measurement contains only the component of the target velocity along the radar line-of-sight (RLOS) and no component of velocity in the perpendicular direction is measured. As a result, existing track initiation algorithms produce a bias in the velocity estimate. This paper first corrects two errors in the single-point (SP) track initialization part of the paper [29] using the range-rate measurement to obtain the initial velocity estimate and associated covariance. Secondly, we present an improved track initiation algorithm based on a heading-parameterized multiple model (HPMM) method that uses the sign of the range-rate measurement, prior knowledge of target maximum speed, and MDV. The proposed algorithm reduces the bias in the initial velocity estimate and the superior performance of the algorithm is demonstrated using Monte Carlo simulations.

[1]  Mahendra Mallick,et al.  Comparison of Single-point and Two-point Difference Track Initiation Algorithms Using Position Measurements , 2008 .

[2]  J. Richards,et al.  GMTI radar minimum detectable velocity. , 2011 .

[3]  Y. Bar-Shalom,et al.  Multi-sensor multi-target tracking using out-of-sequence measurements , 2002, Proceedings of the Fifth International Conference on Information Fusion. FUSION 2002. (IEEE Cat.No.02EX5997).

[4]  B. Pannetier,et al.  Improvement of Multiple Ground Targets Tracking with GMTI Sensor and Fusion of Identification Attributes , 2008, 2008 IEEE Aerospace Conference.

[5]  Anna Freud,et al.  Design And Analysis Of Modern Tracking Systems , 2016 .

[6]  Wolfgang Koch.  Tracking and Sensor Data Fusion: Methodological Framework and Selected Applications , 2013 .

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

[8]  Barbara F. La Scala,et al.  IMM Estimator for Ground Target Tracking with Variable Measurement Sampling Intervals , 2006, 2006 9th International Conference on Information Fusion.

[9]  Taek Lyul Song,et al.  Track Initialization: Prior Target Velocity and Acceleration Moments , 2013, IEEE Transactions on Aerospace and Electronic Systems.

[10]  Michael Mertens,et al.  Tracking and Data Fusion for Ground Surveillance , 2014 .

[11]  Sanjeev Arulampalam,et al.  Comparison of nonlinear filtering algorithms in ground moving target indicator (GMTI) tracking , 2003, SPIE Optics + Photonics.

[12]  Michael Mertens,et al.  Ground target tracking with experimental data of the PAMIR system , 2014, 17th International Conference on Information Fusion (FUSION).

[13]  T. Kirubarajan,et al.  Track segment association, fine-step IMM and initialization with Doppler for improved track performance , 2004, IEEE Transactions on Aerospace and Electronic Systems.

[14]  Wolfgang Koch.  Tracking and Sensor Data Fusion , 2014 .

[15]  N. Peach,et al.  Bearings-only tracking using a set of range-parameterised extended Kalman filters , 1995 .

[16]  P. Veronesi.  Classical Dynamics of Particles and Systems , 1971 .

[17]  T. R. Kronhamn,et al.  Bearings-only target motion analysis based on a multihypothesis Kalman filter and adaptive ownship motion control , 1998 .

[18]  Krishna R. Pattipati,et al.  Ground target tracking with variable structure IMM estimator , 2000, IEEE Trans. Aerosp. Electron. Syst..

[19]  James R. Wertz,et al.  Spacecraft attitude determination and control , 1978 .

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

[21]  Branko Ristic,et al.  Comparison of the particle filter with range-parameterized and modified polar EKFs for angle-only tracking , 2000, SPIE Defense + Commercial Sensing.

[22]  Richard Klemm,et al.  Space-time adaptive processing , 1998 .

[23]  Mark R. Morelande,et al.  Angle-only Filtering in Three Dimensions , 2012 .

[24]  Yaakov Bar-Shalom,et al.  A note on "book review tracking and data fusion: A handbook of algorithms" [Authors' reply] , 2013 .

[25]  W. J. Kenneally,et al.  JointSTARS and GMTI: past, present and future , 1999 .

[26]  M. Mallick,et al.  Maximum likelihood geolocation using a ground moving target indicator (GMTI) report , 2002, Proceedings, IEEE Aerospace Conference.