Xianxiang Yu

Space-Time Transmit Code and Receive Filter Design for Colocated MIMO Radar

This paper deals with the design of multiple-input multiple-output radar space-time transmit code (STTC) and space-time receive filter (STRF) to enhance moving targets detection in the presence of signal-dependent interferences. An iterative procedure, whose convergence is analytically proved, is devised to maximize the Signal to interference plus noise ratio (SINR) accounting for both a similarity constraint and a constant modulus requirement on the probing waveform. Each iteration of the algorithm involves the solution of hidden convex problems. Specifically, both a convex problem (whose solution is provided in closed form) and a set of fractional programming problems, that can be globally solved in polynomial time via the Dinkelbacks procedure, are settled. The computational complexity is linear with the number of iterations and polynomial with the sizes of the STTC and the STRF. In particular, the proposed technique provides a monotonic SINR improvement without limitations on the size of the similarity constraint and ensures convergence to a stationary point filling these important gaps in the open literature. Besides, the reported results highlight that the new devised procedure outperforms both in the optimized SINR value and the computational complexity than the available counterparts.

Local Ambiguity Function Shaping via Unimodular Sequence Design

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 sidelobe 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.

Robust constrained waveform design for MIMO radar with uncertain steering vectors

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.

Space-time transmit code and receive filter design for colocated MIMO radar

This paper considers the design problem of Multiple-Input Multiple-Output (MIMO) radar space-time transmit code (STTC) and space-time receive filter (STRF) for a moving point-like target in the presence of signal-dependent interference. An iterative procedure, whose convergence is analytically proved, is devised to maximize the Signal to Interference plus Noise Ratio (SINR) accounting for both a similarity constraint and constant modulus requirements on the probing waveform. Each iteration of the algorithm, involves the solution of hidden convex problems. Specifically, both a convex problem (whose solution is provided in closed form) and a set of fractional programming problem, that can be globally solved in polynomial time via the Dinkelbacks procedure, are solved. The computational complexity is linear in the number of iterations and polynomial with the sizes of the STTC and the STRF. Finally, numerical results are provided to assess the quality of the devised procedure.

Constant modulus sequence set design with good correlation properties

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.

Exact Distribution for the Product of Two Correlated Gaussian Random Variables

This letter considers the distribution of product for two correlated real Gaussian random variables with nonzero means and arbitrary variances, which arises widely in radar and communication societies. We determine the exact probability density function (PDF) in terms of an infinite sum of modified Bessel functions of second kind, which includes some existent results, i.e., zero-means and/or independent variables, as special cases. Then, we study the approximation error and convergence rate when finite summations are exploited in practice. Finally, we evaluate the PDF behaviors of the derived expression as well as the Monte Carlo simulations.

Fast implementation for modified adaptive multi-pulse compression

This paper deals with the estimation of range-Doppler plane in pulse Doppler radar system, accounting both for clutter-free scenario and clutter scenario. A modified adaptive multi-pulse compression (MAMPC) algorithm including the estimation stages of range dimension and Doppler dimension is proposed for clutter-free scenario, where each stage is implemented based on the gain constraint adaptive pulse compression (GCAPC) algorithm. Additionally, the combination of whitening method removing the correlation of clutter component and MAMPC algorithm is presented for the considered clutter scenario. Numerical simulations are provided to validate the effectiveness of MAMPC in terms of estimation of range-Doppler plane and computation burden.

Constrained transmit beampattern design for colocated MIMO radar

Abstract This paper considers the constrained waveform design for Multiple-Input Multiple-Output (MIMO) radar to synthesize a desired beampattern. Specifically, resorting to SemiDefinite Programming (SDP) related technique, we first minimize Integration Sidelobe Level (ISL) to optimize the waveform covariance matrix enforcing a uniform elemental power restriction as well as a 3dB bandwidth constraint. Then, based on Least Square (LS) approach, we present the existing Cyclic Algorithm (CA) and a new Sequential Iterative Algorithm (SIA) to devise the waveform under a constant modulus constraint, and a similarity constraint to allow the designed waveform sharing the similarity feature with a given reference waveform. In particular, the proposed SIA directly optimizes the objective function and its each iteration turns the multidimensional optimization problem into multiple one-dimensional optimization problems with closed-form solutions. Finally, we assess the effectiveness of the proposed technique through numerical simulations in comparison with CA.

Ambiguity Function design via Accelerated Iterative Sequential Optimization

This paper focuses on the Ambiguity Function design for the unimodular sequence, which is of great interest in radar and communication systems. 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. At the analysis stage, we evaluate the effectiveness of the proposed algorithm in terms of the achieved WISL and computation time with respect to the gradient method using numerical simulations.

Constrained MIMO radar waveform design for beampattern formation

This paper considers the constrained waveform design of Multiple-Input Multiple-Output (MIMO) radar to synthesize a desired beampattern. Specifically, resorting to SemiDefinite Programming (SDP) related technique, we first minimize Integrate Sidelobe Level (ISL) to optimize the waveform covariance matrix forcing a uniform elemental power requirement as well as a 3dB bandwidth constraint. Then, based on Least Square (LS) approach, we devise the waveform accounting for constant modulus and similarity constraints by using cyclic algorithm (CA). Finally, we assess the effectiveness of the proposed technique through numerical simulations.