Effects of Geometry Configurations on Ambiguity Properties for Bistatic MIMO Radar

Bistatic multiple-input multiple-output (MIMO) radar can improve the system performance for obtaining the waveform diversity and larger degrees of freedom (DoF), and efiectively counteract the stealthy target for its transmit antennas and receive antennas separated placement. Similarly with the conventional bistatic radar, the geometry conflgurations of bistatic MIMO radar also play an important role in radar system's performance. Aimed at considering these efiects of geometry conflgurations on the performance for bistatic MIMO radar, in this paper the extended ambiguity function is deflned as the coherent cumulation of the matching output of all channels, where the information of the system geometry conflguration is included in the received signal model. This new ambiguity function can be used to characterize the local and global resolution properties of the whole radar systems instead of only considering transmitted waveforms in Woodward's. In addition, some examples with the varying system conflgurations or target parameters are given to illustrate their efiects, where the spatial stepped-frequency signal set (a quasi-orthogonal waveform set) is used. The simulation results demonstrate that the more approaching monostatic MIMO radar case, the better ambiguity properties of time-delay and Doppler for bistatic MIMO radar.

[1]  Jun Li,et al.  Joint DOD and DOA estimation for bistatic MIMO radar , 2009, Signal Process..

[2]  Yide Wang,et al.  Combined ESPRIT-Rootmusic for DOA-DOD Estimation in Polarimetric Bistatic MIMO Radar , 2011 .

[3]  Daniel R. Fuhrmann,et al.  MIMO Radar Ambiguity Functions , 2006, IEEE Journal of Selected Topics in Signal Processing.

[4]  J. Tabrikian,et al.  Target Detection and Localization Using MIMO Radars and Sonars , 2006, IEEE Transactions on Signal Processing.

[5]  D. Fuhrmann,et al.  Transmit beamforming for MIMO radar systems using partial signal correlation , 2004, Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004..

[6]  Monai Krairiksh,et al.  Two-Probe Excited Circular Ring Antenna for MIMO Application , 2009 .

[7]  P. Stoica,et al.  MIMO Radar Signal Processing , 2008 .

[8]  Paul V. Brennan,et al.  FMCW Based MIMO Imaging Radar for Maritime Navigation , 2011 .

[9]  Guisheng Liao,et al.  Performance Analysis of Beamforming for MIMO Radar , 2008 .

[10]  Klaus Krickeberg,et al.  Probability and information theory II , 1969 .

[11]  L.J. Cimini,et al.  MIMO Radar with Widely Separated Antennas , 2008, IEEE Signal Processing Magazine.

[12]  Hassan M. El-Sallabi,et al.  Effect of Antenna Array Geometry and ULA Azimuthal Orientation on MIMO Channel Properties in Urban Microcells , 2006 .

[13]  H. El-Sallabi,et al.  Effect of Mutual Coupling on Capacity of MIMO Wireless Channels in High SNR Scenario , 2006 .

[14]  P. P. Vaidyanathan,et al.  MIMO Radar Ambiguity Properties and Optimization Using Frequency-Hopping Waveforms , 2008, IEEE Transactions on Signal Processing.

[15]  Rick S. Blum,et al.  MIMO radar: an idea whose time has come , 2004, Proceedings of the 2004 IEEE Radar Conference (IEEE Cat. No.04CH37509).

[16]  H. Urkowitz,et al.  Generalized Resolution in Radar Systems , 1962, Proceedings of the IRE.

[17]  Jun Li,et al.  Erratum to "Multitarget Identification and Localization Using Bistatic MIMO Radar Systems" , 2008, EURASIP J. Adv. Signal Process..

[18]  Hong Gu,et al.  A new method for joint DOD and DOA estimation in bistatic MIMO radar , 2010, Signal Process..

[19]  Alireza Mallahzadeh,et al.  DESIGN OF AN E-SHAPED MIMO ANTENNA USING IWO ALGORITHM FOR WIRELESS APPLICATION AT 5.8 GHZ , 2009 .

[20]  D.W. Bliss,et al.  Multiple-input multiple-output (MIMO) radar: performance issues , 2004, Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004..

[21]  Daniel W. Bliss,et al.  Multiple-input multiple-output (MIMO) radar and imaging: degrees of freedom and resolution , 2003, The Thrity-Seventh Asilomar Conference on Signals, Systems & Computers, 2003.

[22]  Hsi-Tseng Chou,et al.  INVESTIGATIONS OF ISOLATION IMPROVEMENT TECHNIQUES FOR MULTIPLE INPUT MULTIPLE OUTPUT (MIMO) WLAN PORTABLE TERMINAL APPLICATIONS , 2008 .

[23]  Randolph L. Moses,et al.  On the geometry of isotropic arrays , 2003, IEEE Trans. Signal Process..

[24]  Rick S. Blum,et al.  Performance of MIMO radar systems: advantages of angular diversity , 2004, Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004..

[25]  H. Schwarzlander,et al.  Ambiguity function for a bistatic radar , 1992, [1992] Proceedings of the IEEE-SP International Symposium on Time-Frequency and Time-Scale Analysis.

[26]  Arye Nehorai,et al.  Effects of sensor placement on acoustic vector-sensor array performance , 1999 .

[27]  F.C. Robey,et al.  MIMO radar theory and experimental results , 2004, Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004..

[28]  Philip M. Woodward,et al.  Probability and Information Theory with Applications to Radar , 1954 .

[29]  José M. F. Moura,et al.  Ambiguity in radar and sonar , 1998, IEEE Trans. Signal Process..

[30]  Yide Wang,et al.  Polynomial root finding technique for joint DOA DOD estimation in bistatic MIMO radar , 2010, Signal Process..

[31]  Alexander M. Haimovich,et al.  Spatial Diversity in Radars—Models and Detection Performance , 2006, IEEE Transactions on Signal Processing.

[32]  Jian Li,et al.  MIMO Radar with Colocated Antennas , 2007, IEEE Signal Processing Magazine.