GSM passive coherent location system: performance prediction and measurement evaluation

This study describes the processing scheme of the FKIE (Fraunhofer Institute for Communication, Information Processing and Ergonomics) GSM-based passive coherent location (PCL) system, which consists of an antenna and signal processing adapted to the GSM waveform and of target tracking based on multi-hypothesis tracking. To overcome the limitations from a single bistatic transmitter-receiver pair, fusion of the measurements from different geometries is the key component of a GSM PCL system. The authors demonstrate a significant improvement in target position estimation from the tracking process on the basis of real data and theoretical performance bounds. The impact of the transmitter-target-receiver geometry is discussed and the effect of the exploitation of prior context knowledge (e.g. clutter and land maps) on maritime traffic surveillance is shown.

[1]  Klaus Becker Target Motion Analysis (TMA) , 2000 .

[2]  D. Wehner High Resolution Radar , 1987 .

[3]  Kristine L. Bell,et al.  Bayesian Bounds for Parameter Estimation and Nonlinear Filtering/Tracking , 2007 .

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

[5]  Jeffrey K. Uhlmann,et al.  Unscented filtering and nonlinear estimation , 2004, Proceedings of the IEEE.

[6]  Ulrich R. O. Nickel System considerations for passive radar with GSM illuminators , 2010, 2010 IEEE International Symposium on Phased Array Systems and Technology.

[7]  Xin Zhang,et al.  Dynamic Cramer-Rao bound for target tracking in clutter , 2005, IEEE Transactions on Aerospace and Electronic Systems.

[8]  Martin Ulmke,et al.  Exploitation of a priori information for tracking maritime intermittent data sources , 2011, 14th International Conference on Information Fusion.

[9]  M. Ulmke,et al.  Ground target tracking and road map extraction , 2006 .

[10]  Wulf-Dieter Wirth,et al.  Radar Techniques Using Array Antennas , 2001 .

[11]  B. Moran,et al.  Clutter map and target tracking , 2005, 2005 7th International Conference on Information Fusion.

[12]  F. Colone,et al.  Cancellation of clutter and multipath in passive radar using a sequential approach , 2006, 2006 IEEE Conference on Radar.

[13]  H. Kuschel,et al.  On the potentials of passive, multistatic, low frequency radars to counter stealth and detect low flying targets , 2008, 2008 IEEE Radar Conference.

[14]  Scheer,et al.  Principles of Modern Radar: Volume 3: Radar Applications , 2013 .

[15]  P. E. Howland,et al.  FM radio based bistatic radar , 2005 .

[16]  Martina Daun,et al.  Different Tools for Clutter Mapping , 2010, GI Jahrestagung.

[17]  Martina Daun,et al.  Multistatic multihypothesis tracking: Environmentally adaptive and high-precision state estimates , 2008, 2008 11th International Conference on Information Fusion.

[18]  H. Griffiths,et al.  Passive coherent location radar systems. Part 1: performance prediction , 2005 .

[19]  Carlos H. Muravchik,et al.  Posterior Cramer-Rao bounds for discrete-time nonlinear filtering , 1998, IEEE Trans. Signal Process..

[20]  M. Sciotti,et al.  Maritime multi-sensor data association based on geographic and navigational knowledge , 2008, 2008 IEEE Radar Conference.

[21]  R. Zemmari,et al.  Maritime surveillance using GSM passive radar , 2012, 2012 13th International Radar Symposium.

[22]  Martina Daun,et al.  Tracking in multistatic passive radar systems using DAB/DVB-T illumination , 2012, Signal Process..

[23]  H. V. Trees Detection, Estimation, And Modulation Theory , 2001 .

[24]  Reda Zemmari,et al.  GSM passive radar for medium range surveillance , 2009, 2009 European Radar Conference (EuRAD).

[25]  G. V. Keuk Sequential track extraction , 1998 .