This paper deals with the joint design of Multiple-Input Multiple-Output (MIMO) radar transmit waveform and receive filter to enhance multiple targets detectability in the presence of signal-dependent clutter and noise. The worst-case Signal-to-Interference-Noise-Ratio (SINR) over multiple targets is explicitly maximized. To ensure hardware compatibility and coexistence between MIMO radar and other wireless systems, constant modulus and spectral restrictions on the waveform are incorporated in our design. A max-min non-convex optimization problem emerges as a function of the transmit waveform, which we solve via a novel polynomial-time iterative procedure that involves solving a sequence of convex problems with constraints that evolve with every iteration. The overall algorithm follows an alternate optimization over the receive filter and transmit waveform. For the problem of waveform optimization (which is our central contribution), we provide analytical guarantees of monotonic cost function improvement with proof of convergence to a solution that satisfies the KarushKuhnTucker (KKT) conditions. We also develop extensions that address the well-known waveform similarity constraint. By simulating challenging practical scenarios, we evaluate the proposed algorithm against the state-of-the-art methods in terms of the achieved SINR value and the computational complexity. Overall, we show that our proposal outperforms state of the art competing methods while providing the most favorable performance-complexity balance.

This paper deals with the robust waveform design of Multiple-Input Multiple-Output (MIMO) radar to improve target detectability embedded in signal-dependent interferences. Two iterative algorithms with ensuring convergence properties are introduced to maximize the worst case Signal-to-Interferenceplus-Noise Ratio (SINR) over steering matrix mismatches under the constant modulus and similarity constraints. Each iteration of the proposed algorithms splits the high dimensional problem into multiple one dimensional problems, to which the optimal solutions can be found in polynomial times. Numerical examples are provided to assess the capabilities of the proposed techniques in comparison with the existing methods in terms of the SINR and the computational times for both the continuous and discrete phase cases of the probing signal

This letter focuses on the local ambiguity function shaping through unimodular sequence design. An Accelerated Iterative Sequential Optimization (AISO) algorithm is proposed to minimize the average value of the weighted integrated side-lobe level (WISL) over specific Doppler bins and range bins of interest. We evaluate the effectiveness of the AISO algorithm in terms of its achieved WISL and computational complexity in comparison with the gradient method via numerical examples.The capability of using the design to detect high-speed targets is also evaluated.

This paper deals with the joint design of Multiple-Input Multiple-Output (MIMO) Space-Time Transmit Code (STTC) and Space-Time Receive Filter (STRF) to improve the detectability of a moving target embedded in signal-dependent clutter in the presence of uncertainties on the target azimuth angle and Doppler frequency. The Signal to Interference plus Noise Ratio (SINR) is considered as a figure of merit to maximize and multiple restrictions on STTC are forced at the design stage, i.e., similarity and modulus constraints as well as a uniform power requirement among the transmit antennas. To deal with the resulting non-convex design problem, a novel polynomial-time iterative procedure based on Successive Greedy Optimization (SGO) framework ensuring that SINR monotonically increases and converges to a finite value, is developed. Each iteration of the proposed algorithm involves the generalized eigenvalue decomposition to design STRF and a nested iterative technique involving Dinkelbach's procedure and an Alternating Direction Penalty Method (ADPM) to obtain STTC. Numerical results are provided to assess the performance of the proposed algorithm against some counterparts in terms of the optimized SINR value and computational complexity.

Long time coherent integration (LTCI) technique enhances radar detection of maneuvering weak targets. Unfortunately, range migration (RM) and Doppler frequency migration (DFM) would occur during the integration period. Existing LTCI methods are all based on the assumption that the target is of single motion model (i.e., the target's motion model is fixed) during the long integration time. However, with increasing target's maneuverability and long observation time (needed to detect weak targets), the target's motion model is often changing (i.e., target is of multiple motion models) during the integration time, which would reduce the performance of existing LTCI methods significantly. In this paper, we address the LTCI problem for detecting a maneuvering weak target with multiple motion models, where the target signal model is first established. Thereafter, the short-time generalized Radon Fourier transform (STGRFT) based LTCI algorithm is proposed. The STGRFT method could not only eliminate RM and DFM, but also estimate the model-changing point (i.e., the time when target's motion model changes) and accumulate the target energy distributed in different motion stages (corresponding to different motion models). Finally, numerical and real-data experiments are carried out to demonstrate its effectiveness. The results confirm that in terms of integration gain, input-output signal-to-noise ratio (SNR) performance and detection ability, STGRFT-based method is superior to the existing popular LTCI algorithms.

This paper focuses on the joint synthesis of constant envelope transmit signal and receive filter aimed at optimizing radar performance in signal-dependent interference and spectrally contested-congested environments. To ensure the desired Quality of Service (QoS) at each communication system, a precise control of the interference energy injected by the radar in each licensed/shared bandwidth is imposed. Besides, along with an upper bound to the maximum transmitted energy, constant envelope (with either arbitrary or discrete phases) and similarity constraints are forced to ensure compatibility with amplifiers operating in saturation regime and bestow relevant waveform features, respectively. To handle the resulting NP-hard design problems, new iterative procedures (with ensured convergence properties) are devised to account for continuous and discrete phase constraints, capitalizing on the Coordinate Descent (CD) framework. Two heuristic procedures are also proposed to perform valuable initializations. Numerical results are provided to assess the effectiveness of the conceived algorithms in comparison with the existing methods.