Braham Himed

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This paper addresses target detection in passive multiple-input multiple-output (MIMO) radar networks comprised of non-cooperative transmitters and multichannel receivers. A generalized likelihood ratio test is derived, and approximate test statistic distributions are presented for both hypotheses under common scenario conditions. Analysis and simulation(More)
This paper considers the problem of detecting a multichannel signal in the presence of spatially and temporally colored disturbance. A parametric generalized likelihood ratio test (GLRT) is developed by modeling the disturbance as a multichannel autoregressive (AR) process. Maximum likelihood (ML) parameter estimation underlying the parametric GLRT is(More)
We present a statistical analysis of the recently proposed non-homogeneity detector (NHD) for Gaussian interference statistics. Specifically, we show that a formal goodness-of-fit test can be constructed by accounting for the statistics of the generalized inner product (GIP) used as the NHD test statistic. The normalized-GIP follows a central-F distribution(More)
In this paper, we propose co-prime arrays for effective direction-of-arrival (DOA) estimation. To fully utilize the virtual aperture achieved in the difference co-array constructed from a co-prime array structure, sparsity-based spatial spectrum estimation technique is exploited. Compared to existing techniques, the proposed technique achieves better(More)
The detection of moving objects on the ground by airborne radar is one application of space-time adaptive processing (STAP). The goal is to estimate the position and velocity of objects. This paper considers the problem as a linear inverse problem and uses &#x2113;<inf>1</inf>-norm regularization to promote sparsity in the solution. It is proposed that the(More)
We jointly design the transmit and receive beamforming based on a-priori information on the locations of target and interferences in an active array, where each transmit element emits the same waveform up to a complex scalar. A sequential optimization algorithm is proposed to maximize the output signal-to-interference-plus-noise ratio (SINR). Numerical(More)
In this paper, we examine the time-frequency representation (TFR) and sparse reconstruction of non-stationary signals in the presence of missing data samples. These samples lend themselves to missing entries in the instantaneous auto-correlation function (IAF) which, in turn, induce artifacts in the time-frequency distribution and ambiguity function. The(More)