Waveform optimization for random-phase radar signals with PAPR constraints

Transmitting waveforms that are designed in real time to best deal with the interference environment has been shown to provide significant performance benefits. Most previous works has assumed a line-of-sight propagation model. In this paper we build on previous work in waveform optimization for multiple-input, multiple-output radar systems for the case where the signal, during propagation, under goes phase perturbations. In this paper we consider waveform design with the peak-to-average power ratio (PAPR), an issue of practical importance. Furthermore, we couple the design of the waveform with an adaptive receiver and obtain, simultaneously, the weights in an adaptive adaptive matched filter. An example of a clutter and target model is provided to show how the optimal waveform design improves the detection performance of a random-phase radar compared to traditional waveforms.

[1]  Daniel Pérez Palomar,et al.  Code Design for Radar STAP via Optimization Theory , 2010, IEEE Transactions on Signal Processing.

[2]  P. P. Vaidyanathan,et al.  MIMO Radar Waveform Optimization With Prior Information of the Extended Target and Clutter , 2009, IEEE Transactions on Signal Processing.

[3]  Antonio De Maio,et al.  Design of Optimized Radar Codes With a Peak to Average Power Ratio Constraint , 2011, IEEE Transactions on Signal Processing.

[4]  Zhi-Quan Luo,et al.  Semidefinite Relaxation of Quadratic Optimization Problems , 2010, IEEE Signal Processing Magazine.

[5]  Sandeep Gogineni,et al.  Frequency-Hopping Code Design for MIMO Radar Estimation Using Sparse Modeling , 2012, IEEE Transactions on Signal Processing.

[6]  Xiaohua Zhu,et al.  Adaptive Waveform Design for Separated Transmit/Receive ULA-MIMO Radar , 2010, IEEE Transactions on Signal Processing.

[7]  B. Friedlander,et al.  Waveform Design for MIMO Radars , 2007, IEEE Transactions on Aerospace and Electronic Systems.

[8]  A. Nehorai,et al.  Information Theoretic Adaptive Radar Waveform Design for Multiple Extended Targets , 2007, IEEE Journal of Selected Topics in Signal Processing.

[9]  Yingning Peng,et al.  MIMO Radar Waveform Design in Colored Noise Based on Information Theory , 2010, IEEE Transactions on Signal Processing.

[10]  Heung-No Lee,et al.  Multimode Precoding for MIMO Systems: Performance Bounds and Limited Feedback Codebook Design , 2008, IEEE Transactions on Signal Processing.

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

[12]  Jian Li,et al.  Range Compression and Waveform Optimization for MIMO Radar: A CramÉr–Rao Bound Based Study , 2007, IEEE Transactions on Signal Processing.

[13]  James Ward,et al.  Space-time adaptive processing for airborne radar , 1998 .

[14]  Arye Nehorai,et al.  OFDM MIMO Radar With Mutual-Information Waveform Design for Low-Grazing Angle Tracking , 2010, IEEE Transactions on Signal Processing.

[15]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.

[16]  Raviraj S. Adve,et al.  Joint waveform optimization and adaptive processing for random-phase radar signals , 2014, RadarCon 2014.