Multiple-input multiple-output (MIMO) radar is a new concept with some new characteristics, such as multiple orthogonal waveforms and omnidirectional coverage. Based on Stein's lemma, we use relative entropy as a precise and general measure of error exponent to study detection performance for both MIMO radar and phased array radar. And based on derived analytical results, we further study the system configuration problem of Bistatic MIMO radar systems, where transmitters and receivers are located in different positions. Some interesting results are presented. For phased array radar, when the total numbers of transmitters and receivers are fixed, we should always make the number of transmitters equal to the number of receivers. For MIMO radar, we should use a small number of transmitters in low signal noise ratio (SNR) region, and make the number of transmitters equal to the number of receivers in high SNR region. These results are instructive for deployment of bistatic MIMO radar systems in the future.MIMO radar, relative entropy, system configuration

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Rotating object model is commonly used for imaging analysis in high resolution radars such as the inverse synthetic aperture radar (ISAR). For a rotating object, it is known that multi-aspect observations can improve cross-range resolution with the known imaging geometry. For the non-cooperative rotating object with unknown imaging geometry, this paper proposes an integrated scheme to estimate the key parameters, e.g., the rotating velocity and the aspect angle difference between every two observations. Furthermore, convolution back-projection (CBP) method is applied to provide fused imaging result with improved resolution. Also, the accuracy of the ultimate parameter estimation is analyzed, which is strongly related with several important factors like position extraction error of scattering centers and so on. Finally, the results of numerical experiments are provided to demonstrate the effectiveness of the proposed method. CitationYe C M, Xu J, Peng Y N, et al. Key parameter estimation for radar rotating object imaging with multi-aspect observations.

By using spatial diversity, multiple-input-multiple-output (MIMO) radar can improve detection performance for fluctuating targets. In this paper, we propose a spatial fluctuation target model for MIMO radar, where targets are classified as non-fluctuating target, Rayleigh target and Rician target. Based on Stein's lemma, we use relative entropy to study detection performance of optimum detector for Rician target. It is found that in low signal noise ratio (SNR) region, the performance improvement of MIMO radar for detecting Rician target depends on array gain, which is related to the number of receivers. In high SNR region, the improvement of performance depends on diversity gain, which is related to the product of the number of receivers and the number of transmitters. The conclusions of this paper are important for designing MIMO radar system.

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