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Abstract: MIMO radar with properly placed antennas that employs a coherent processing approach can provide superior MSE performance, as indicated by recent work. This paper demonstrates that the magnitude of these gains decreases with an increase in the product of the number of transmit and receive antennas if the antennas for the noncoherent system are also suitably placed, using a placement which is generally different from the one for the coherent processing approach. Initially, we study the systems without constraining the complexity and energy, where each added transmit antenna employs a fixed energy so that the total transmitted energy is allowed to increase as we increase the number of transmit antennas. Later we also look at constrained systems, where adding a transmit antenna splits the total system energy and the total number of antennas employed is restricted. A rigorous theorem is presented for the case of orthogonal signals in temporally and spatially white clutter-plus-noise, but numerical results for nonorthogonal signals and colored clutter-plus-noise follow a similar pattern. [Copyright &y& Elsevier]

• Signal structure is explored to improve detection performance of passive MIMO radar. • Two generalized likelihood ratio tests are derived with unknown covariance matrix. • The proposed tests are shown to be constant false alarm rate. • The proposed tests can approach the optimum performance with known covariance matrix. In passive multiple input multiple output (MIMO) radar, the transmit signals of the noncooperative illuminators of opportunity are usually not completely known. However, they are often standard communication signals with some specific signal structure. Exploiting such information, the detection performance of passive MIMO radar can be improved. In this paper we derive a generalized likelihood ratio test (GLRT) for passive MIMO radar detection when the covariance matrix of the colored Gaussian noise is unknown and the structure of the transmit signal is known but it contains some unknown information bits. Moreover, a model which employs a reasonable approximation for some practical scenarios while requiring only a limited number of training samples is also considered, and a GLRT for this model is also derived. Our tests are shown to be constant false alarm rate (CFAR), and their performance approaches the optimum performance with known signal structure and known covariance matrix when the number of training samples is increased. Finally, several numerical examples are presented to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

• Rigorously develop the Multi-snapshot NOMP (MNOMP). • Provide a stopping criterion based on overestimating probability. • Analyze the convergence of MNOMP. • Show a near-optimal performance of MNOMP. In this paper, multi-snapshot Newtonized orthogonal matching pursuit (MNOMP) algorithm is proposed to deal with the line spectrum estimation with multiple measurement vectors (MMVs). MNOMP has the low computation complexity and state-of-the-art performance advantage of NOMP, and also includes two key steps: Detecting a new sinusoid on an oversampled discrete Fourier transform (DFT) grid and refining the parameters of already detected sinusoids to avoid the problem of basis mismatch. We provide a stopping criterion based on the overestimating probability of the model order. In addition, the convergence of the proposed algorithm is also proved. Finally, numerical results are conducted to show that the performance of MNOMP benefits from MMVs, and the effectiveness of MNOMP when compared against the state-of-the-art algorithms in terms of frequency estimation accuracy and computation complexity. [ABSTRACT FROM AUTHOR]

Most image or video fusion quality metrics are designed to evaluate different video fusion methods for spatial-temporal extraction. And there is limited research on the evaluation of spatial-temporal consistency. In this paper, a video fusion quality metric is proposed to evaluate different fusion methods for spatial-temporal consistency, where spatial-temporal phase congruency is employed as a feature to be compared and 3D zero-mean normalized cross-correlation is employed as the similarity measure. Firstly, the spatial-temporal phase congruency maps for input and fused videos are computed using a set of predefined 3D Log-Gabor filters. Then the spatial-temporal phase congruency maps are divided into many non-overlapped spatial-temporal blocks and a local block-based quality metric is defined by performing 3D zero-mean normalized cross-correlation on the relevant spatial-temporal phase congruency maps of the input and fused videos. Finally, the global quality metric is constructed as the weighted average of all the block-based quality metrics. The required local and global weights are defined by the spatial-temporal structure tensor. Several sets of experiments demonstrate the validity and feasibility of the proposed metric. Moreover, the proposed metric shows higher stability and robustness than some other metrics in a noisy environment. [ABSTRACT FROM AUTHOR]

This paper considers the localization of an emitter employing linear frequency modulation (LFM) signal with unknown parameters. The proposed approach is based on jointly estimating the emitter position along with the transmitted signal parameters. In the maximum likelihood context, the joint estimation problem is shown to translate into an optimization search in a six-dimensional space. In many practical applications, such a search may be too computationally expensive to run in real-time. We suggest a sub-optimal yet fast solution based on combining the direct position determination (DPD) method with a short time Fourier transform (STFT). Despite the sub-optimality, the proposed DPD-STFT method is able, with low complexity, to achieve higher localization accuracies than methods that are based on estimation of emitter position only (regardless of signal parameters). Indeed, due to joint estimation of emitter position and the transmitted signal parameters, our method harnesses more information for localization purposes. Simulation results show that the proposed method outperforms the existing DPD algorithms, in terms of localization error. [ABSTRACT FROM AUTHOR]