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Multiple-input multiple-output (MIMO) radar design for extended targets in a spectrally crowded environment is a challenge owing to the high sensitivity of the target impulse response (TIR) and the increasing requests for spectrum. Assuming unknown TIR, this paper proposes a joint design method to optimize the transmit waveforms and receive filter bank in MIMO structure ensuring spectral compatibility with the overlayed radiators. A priori information is used to impose a spectral constraint on the waveforms, which is the result of a non-convex optimization problem aimed at enhancing the average signal-to-interference-plus-noise-ratio (SINR) over a finite uncertainty set for the TIR. The new method realizes an improved spectral cohabitation with the surrounding radiators through an appropriate modulation of the transmitted energy. In addition, we develop an iterative optimization algorithm which successively enhances the average SINR. Each iteration of the algorithm involves a hidden convex problem, which can be solved resorting to the rank-one decomposition procedure. Finally, the performance is assessed by studying the trade-off among the achieved SINR and spectral shape. The reported results are presented to analyze the performance of the devised method against several counterparts in terms of the SINR value and robustness. [ABSTRACT FROM AUTHOR]

Assuming unknown knowledge of target impulse response (TIR), this paper develops robust design methods to optimize the transceiver for the detection of extended targets in the presence of signal-dependent interference. Two different transceiver design schemes comprising single filter and multiple filters methods are presented to handle the fact that the TIR of extended target is unknown at the transmit side. The lowest signal to interference plus noise ratio (SINR) is considered at the receiver side as the performance measure of the system. Two robust design problems are formulated as max-min optimization problems to robustify the system SINR with respect to the unknown TIR. The former is solved using an iterative optimization process alternating between two sequential semi-definite programming (SDP) problems; the latter is solved employing an iterative optimization procedure alternating between a convex and a generalized fractional programming problems. Finally, several numerical examples highlight that the proposed design schemes have better robustness compared to several counterparts which are presented in open literature.

We focus on the robust joint design of the transmit waveform and filtering structure for polarimetric radar. Considering the worst case signal-to-interference plus noise ratio (SINR) at the output as the figure of merit to optimize under both a similarity and an energy constraint on the transmit signal, we develop an iterative optimization procedure. The effectiveness of the proposed method is validated through experimental results, underlining the performance improvement given by a full-polarimetric design. [ABSTRACT FROM AUTHOR]

We propose a novel robust design method to jointly optimize the radar transmit code and receive filter, exploiting the Signal-to-Interference plus Noise Ratio (SINR) at the receiver end as design figure of merit. We confer robustness to our method against uncertainties on the target impulse response (TIR) using a worst-case optimization approach based on two different uncertainty sets. The former is composed of a finite collection of TIRs, obtained by sampling the actual TIR at some aspect angles; the latter is a spherical uncertainty set. We further enforce a peak-to-average power ratio (PAR) constraint to the transmit code, which is very important for radar applications where the transmitter operates close to saturation. The design problem is tackled using a sequential optimization procedure alternating between two semi-definite programming (SDP) problems, followed by randomization steps. Our numerical results highlight the robustness and applicability of the proposed method in different scenarios. [ABSTRACT FROM PUBLISHER]