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This paper considers the design problem of constant modulus sequence set which could be applied in multiple-input multiple-output (MIMO) radar and communication societies, to achieve desired correlation properties.A new and general weighted integrated sidelobe level (WISL) accounting for both auto- and cross-correlation functions is proposed.An iteration algorithm based on iteration direct search is devised to optimizes the WISL without limitations on the weightslling the gap in the open literature and involves the FFT operation at each iteration ensuring the convergence speed.Results highlight that the proposed algorithm possesses excellent superiority both in correlation properties and computation complexity compared with the related WeCAN algorithm. This paper considers the design problem of constant modulus sequence set which could be applied in multiple-input multiple-output (MIMO) radar and communication societies, to achieve desired correlation properties. An iteration algorithm based on iteration direct search is devised to minimize a new and general weighted integrated sidelobe level (WISL) accounting for both auto- and cross-correlation functions. At each iteration of the proposed algorithm, we sequentially optimize each code element of the sequence while fixing remained code elements; to this end, we split the multi-dimensional problem into multiple one-dimension problems with closed-form solutions for continues phase case and optimal solutions for finite phase case via one-dimensional search. In particular, the proposed algorithm directly optimizes the WISL without limitations on the weights filling the gap in the open literature and involves the FFT operation at each iteration ensuring the convergence speed. The numerical simulations validate the effectiveness of the proposed algorithm.

Radar signal design in a spectrally crowded environment is a very challenging and topical problem due to the increasing demand for both military surveillance/remote-sensing capabilities and civilian wireless services. This paper deals with the synthesis of optimized radar waveforms ensuring spectral compatibility with the overlayed licensed electromagnetic radiators. A priori information, for instance, provided by a radio environmental map (REM), is exploited to force a spectral constraint on the radar waveform, which is thus the result of a constrained optimization process aimed at improving some radar performances (such as detection, sidelobes, resolution, tracking). The feasibility of the waveform optimization problem is extensively studied, and a solution technique leading to an optimal waveform is proposed. The procedure requires the relaxation of the original problem into a convex optimization problem and involves a polynomial computational complexity. At the analysis stage, the waveform performance is studied in terms of trade-off among the achievable signal to interference plus noise ratio (SINR), spectral shape, and the resulting autocorrelation function (ACF). © 2014 IEEE.

The work presented here focuses on the performance analysis of the sidelobe blanking (SLB) system with noncoherent integration in the presence of white Gaussian noise and jammer entering through the sidelobes of the antenna. Closed-form performance probabilities, in terms of either the generalized Marcum or Nuttall Q-function, are derived for nonfluctuating target and jammer, both in the blanking and the detection regions. The analysis is then extended to account for arbitrary correlated, possibly nonidentically distributed, fluctuating target and/or jamming returns among a given number of integrated pulses. Finally, several numerical results are given, and the effects of typical SLB parameters are discussed.

In this study, the authors consider the problem of cognitive transmit signal and receive filter design for a point-like target embedded in a high-reverberating environment. The authors focus on phase-only waveforms, sharing either a continuous or a finite alphabet phase, hence they devise constrained optimisation procedures that sequentially improve the Signal to Interference plus Noise Ratio (SINR), accounting for a similarity constraint between the transmitted signal and a prescribed radar waveform. The computational complexity of the proposed algorithms is linear with the number of iterations and polynomial with the receive filter length. At the analysis stage, the performance of the techniques is assessed in the presence of a homogeneous clutter scenario.

This correspondence considers the problem of robust waveform design in the presence of colored Gaussian disturbance under a similarity and an energy constraint. We resort to a max-min approach, where the worst case detection performance (over the possible Doppler shifts) is optimized with respect to the radar waveform under the previously mentioned constraints. The resulting optimization problem is a non-convex Quadratically Constrained Quadratic Program (QCQP) with an infinite number of constraints, which is NP-hard in general and typically difficult to solve. Hence, we propose an algorithm with a polynomial computational complexity to generate a good sub-optimal solution for the aforementioned QCQP. The analysis, conducted in comparison with some known radar waveforms, shows that the sub-optimal solutions by the algorithm lead to high-quality radar signals.

This paper considers the robust waveform design of multiple-input multiple-output (MIMO) radar to enhance targets detection in the presence of signal-dependent interferences assuming the knowledge of steering vectors is imprecise. Specifically, resorting to semidefinite programming (SDP)-related technique, we first maximize the worst-case signal-to-interference-plus-noise ratio (SINR) over uncertain region to optimize waveform covariance matrix forcing a uniform elemental power requirement. Then, based on least square (LS) approach, we devise the waveform accounting for constant modulus and similarity constraints by the obtained waveform covariance matrix using cyclic algorithm (CA). Finally, we assess the effectiveness of the proposed technique through numerical simulations in terms of non-uniform point-like clutter and uniform clutter.