MIMO radar waveform optimization with prior information of the extended target and clutter
IEEE Transactions on Signal Processing
Communications-inspired sensing: a case study on waveform design
IEEE Transactions on Signal Processing
Clutter rank of STAP in MIMO radar with waveform diversity
IEEE Transactions on Signal Processing
Phased-MIMO radar: a tradeoff between phased-array and MIMO radars
IEEE Transactions on Signal Processing
MIMO radar, SIMO radar, and IFIR radar: a comparison
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
Reduced complexity angle-Doppler-range estimation for MIMO radar that employs compressive sensing
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
Nested arrays: a novel approach to array processing with enhanced degrees of freedom
IEEE Transactions on Signal Processing
MIMO radar waveform design in colored noise based on information theory
IEEE Transactions on Signal Processing
MIMO radar detection and adaptive design under a phase synchronization mismatch
IEEE Transactions on Signal Processing
Receiver design for MIMO radar range sidelobes suppression
IEEE Transactions on Signal Processing
Tensor algebra and multidimensional harmonic retrieval in signal processing for MIMO radar
IEEE Transactions on Signal Processing
Performance comparison of airborne phased-array and mimo radar with subarrays
Journal of Mobile Multimedia
Maximum likelihood estimation of DOD and DOA for bistatic MIMO radar
Signal Processing
Hi-index | 35.71 |
In the traditional transmitting beamforming radar system, the transmitting antennas send coherent waveforms which form a highly focused beam. In the multiple-input multiple-output (MIMO) radar system, the transmitter sends noncoherent (possibly orthogonal) broad (possibly omnidirectional) waveforms. These waveforms can be extracted at the receiver by a matched filterbank. The extracted signals can be used to obtain more diversity or to improve the spatial resolution for clutter. This paper focuses on space-time adaptive processing (STAP) for MIMO radar systems which improves the spatial resolution for clutter. With a slight modification, STAP methods developed originally for the single-input multiple-output (SIMO) radar (conventional radar) can also be used in MIMO radar. However, in the MIMO radar, the rank of the jammer-and-clutter subspace becomes very large, especially the jammer subspace. It affects both the complexity and the convergence of the STAP algorithm. In this paper, the clutter space and its rank in the MIMO radar are explored. By using the geometry of the problem rather than data, the clutter subspace can be represented using prolate spheroidal wave functions (PSWF). A new STAP algorithm is also proposed. It computes the clutter space using the PSWF and utilizes the block-diagonal property of the jammer covariance matrix. Because of fully utilizing the geometry and the structure of the covariance matrix, the method has very good SINR performance and low computational complexity.