Extended Target Recognition in Cognitive Radar Networks

We address the problem of adaptive waveform design for extended target recognition in cognitive radar networks. A closed-loop active target recognition radar system is extended to the case of a centralized cognitive radar network, in which a generalized likelihood ratio (GLR) based sequential hypothesis testing (SHT) framework is employed. Using Doppler velocities measured by multiple radars, the target aspect angle for each radar is calculated. The joint probability of each target hypothesis is then updated using observations from different radar line of sights (LOS). Based on these probabilities, a minimum correlation algorithm is proposed to adaptively design the transmit waveform for each radar in an amplitude fluctuation situation. Simulation results demonstrate performance improvements due to the cognitive radar network and adaptive waveform design. Our minimum correlation algorithm outperforms the eigen-waveform solution and other non-cognitive waveform design approaches.

[1]  Alexander G. Tartakovsky.  Asymptotically optimal sequential tests for nonhomogeneous processes , 1998 .

[2]  M.A. Neifeld,et al.  Adaptive Waveform Design and Sequential Hypothesis Testing for Target Recognition With Active Sensors , 2007, IEEE Journal of Selected Topics in Signal Processing.

[3]  S. Haykin.  Cognitive Radar Networks , 2006, Fourth IEEE Workshop on Sensor Array and Multichannel Processing, 2006..

[4]  Pramod K. Varshney,et al.  Multisensor Data Fusion , 1997, IEA/AIE.

[5]  Joseph A. O'Sullivan,et al.  Automatic target recognition using sequences of high resolution radar range-profiles , 2000, IEEE Trans. Aerosp. Electron. Syst..

[6]  Arye Nehorai,et al.  Target Detection in Clutter Using Adaptive OFDM Radar , 2009, IEEE Signal Processing Letters.

[7]  R. Khan,et al.  Sequential Tests of Statistical Hypotheses. , 1972 .

[8]  Hsueh-Jyh Li,et al.  Using range profiles as feature vectors to identify aerospace objects , 1993 .

[9]  Mengdao Xing,et al.  Radar HRRP target recognition based on higher order spectra , 2005, IEEE Transactions on Signal Processing.

[10]  Richard Alan Mitchell.  Robust high range resolution radar target identification using a statistical feature based classifier with feature level fusion , 1997 .

[11]  Aleksandar Dogandzic,et al.  Generalized multivariate analysis of variance - A unified framework for signal processing in correlated noise , 2003, IEEE Signal Process. Mag..

[12]  Mark R. Bell.  Information theory and radar waveform design , 1993, IEEE Trans. Inf. Theory.

[13]  Evaggelos Geraniotis,et al.  Robust data fusion for multisensor detection systems , 1990, IEEE Trans. Inf. Theory.

[14]  Dante C. Youla,et al.  Optimum transmit-receiver design in the presence of signal-dependent interference and channel noise , 1999, Conference Record of the Thirty-Third Asilomar Conference on Signals, Systems, and Computers (Cat. No.CH37020).

[15]  Zheng Bao,et al.  Multi-aspect radar target recognition method based on scattering centers and HMMs classifiers , 2005, IEEE Transactions on Aerospace and Electronic Systems.

[16]  A. Zyweck,et al.  Radar target classification of commercial aircraft , 1996, IEEE Transactions on Aerospace and Electronic Systems.

[17]  James Llinas,et al.  Multisensor Data Fusion , 1990 .

[18]  Huadong Meng,et al.  Adaptive single-tone waveform design for target recognition in Cognitive Radar , 2009 .

[19]  N.A. Goodman,et al.  Adaptive waveforms for target class discrimination , 2007, 2007 International Waveform Diversity and Design Conference.

[20]  Joseph R. Guerci,et al.  Theory and application of optimum transmit-receive radar , 2000, Record of the IEEE 2000 International Radar Conference [Cat. No. 00CH37037].

[21]  Qilian Liang,et al.  Radar Sensor Networks: Algorithms for Waveform Design and Diversity with Application to ATR with Delay-Doppler Uncertainty , 2007, EURASIP J. Wirel. Commun. Netw..

[22]  R. Srinivasan.  Distributed radar detection theory , 1986 .

[23]  Kyung-Tae Kim,et al.  Two-dimensional scattering center extraction based on multiple elastic modules network , 2003 .

[24]  D. J. Salmond,et al.  Track maintenance using measurements of target extent , 2003 .

[25]  Z. Bao,et al.  Properties of high-resolution range profiles , 2002 .

[26]  William C. Lindsey.  Improvements to be Realized Through the Use of Block-Coded Communication Systems , 1966, IEEE Transactions on Aerospace and Electronic Systems.

[27]  S. Haykin,et al.  Cognitive radar: a way of the future , 2006, IEEE Signal Processing Magazine.