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In this paper, we investigate a novel framework on the waveform optimization for multiple-input multiple-output (MIMO) radar systems under assumptions of statistical information of scattering matrices and colored noise. Different from most of traditional designs under total power constraint, in our framework, a general power constraint named as multiple weighted power constraints is provided, which includes total power constraint, per-antenna power constraints as its special cases. In the framework, the transmit and receive correlations of parameter matrix to estimate and the spatial and time correlations of noise matrix are all taken into account. Moreover, the signal-dependent interference is also taken into account, which can be considered as a self-interference noise. Based on the available statistics of scattering matrices and colored noise, two kinds of estimation schemes are proposed in this paper, which can realize different trade-offs between complexity and performance. Finally, some numerical results are given to demonstrate the performance advantages of the proposed radar waveform designs.

The relationship of different optimal waveform design criteria in signal-dependent interference, as well as additive channel noise for stochastic extended target, is investigated here. Within constraints on waveform energy and bandwidth, the optimal waveform design based on the signal-to-interference plus noise ratio criterion, probability of detection criterion, and mutual information criterion are modelled. Afterwards, the relationship of these criteria is presented. Simulations are conducted to illustrate that under the same bandwidth and energy constraints, the three criteria lead to the similar optimal waveform. The energy of optimal waveform can be distributed in some narrow bands where target power is large and interference power is small.

The relationship of different optimal waveform design criteria in signal-dependent interference, as well as additive channel noise for stochastic extended target, is investigated here. Within constraints on waveform energy and bandwidth, the optimal waveform design based on the signal-to-interference plus noise ratio criterion, probability of detection criterion, and mutual information criterion are modelled. Afterwards, the relationship of these criteria is presented. Simulations are conducted to illustrate that under the same bandwidth and energy constraints, the three criteria lead to the similar optimal waveform. The energy of optimal waveform can be distributed in some narrow bands where target power is large and interference power is small. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of the spectrally compatible waveform design for multiple-input multiple-output (MIMO) radar in the presence of multiple targets and signal-dependent interference. Unlike the existing approaches to designing the waveform for a single target via output signal-to-interference-plus-noise ratio (SINR) maximization, a new method is proposed to deal with a more general problem, i.e., designing a spectrally compatible waveform for multiple targets, by minimizing the waveform energy of the overlayed space-frequency bands under constraints of waveform similarity and individual SINR requirements. Due to the existence of signal dependence, the formulated optimization problem is NP-hard. Toward this end, an iterative algorithm is developed. Concretely, at each iteration, the receive filter is first obtained with the aid of the minimum variance distortionless response method, then the transmit waveform is optimized by employing the dual ascent method. Both the convergence and asymptotic optimality of this algorithm are discussed. Numerical simulations are provided to demonstrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

This paper focuses on the robust transmitter–receiver design to improve the detectability of an extended target embedded in signal-dependent interference. Specifically, we allow uncertainties for both the interference and target impulse responses. An iterative algorithm is proposed to sequentially improve the worst-case Signal-to-Interference-plus-Noise Ratio (SINR) under the constant modulus constraint. Each iteration involves two max-min problems, which can be efficiently solved by generalized eigenvalue decomposition and the Dinkelbach’s procedure, respectively, to obtain the optimized receive filter vector and unimodular transmit sequence. The effectiveness of the proposed method is confirmed numerically in terms of the optimized SINR. We also highlight the improvements of the worst-case SINR compared to nominal designs without robustness considerations. [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]