Yongbo Zhao

Target spatial and frequency scattering diversity property for diversity MIMO radar

Statistical multiple-input multiple-output (MIMO) radar, e.g., frequency diversity MIMO radar (FDMR) and spatial diversity MIMO radar (SDMR), can exploit signal diversity to improve target detection performance. The statistical property of target echo signals received in diversity channels is an important concern in designing signal processing algorithms for an FDMR and an SDMR, which is studied in this paper by using a round shaped scatterers centre target model. A uniform formula is derived to estimate the correlation coefficients of target echo signals in diversity channels for both an FDMR and an SDMR. The theoretical correlation coefficients are testified by numerical experiments.

Image denoising algorithm using doubly local Wiener filtering with block-adaptive windows in wavelet domain

In this paper, we propose the block-adaptive windows that are used to upgrade the image denoising performance of the doubly local Wiener filtering method and the corresponding algorithm is also used to reduce spatially non-stationary additive white Gaussian noise (SNS-AWGN) in images. Based on the fact that the energy clusters in the detail subimages of an image exhibit direction features varying with spatial locations and oriented subbands, a noisy detail subimage is divided into non-overlapping small-size blocks and the spatial energy correlation function of each block is calculated to determine the principal direction of energy clusters within each block and the corresponding block-adaptive window. The block-adaptive windows are used to improve the estimations of the images energy distribution in the detail subimages. For noisy images corrupted by SNS-AWGNs, non-uniform noise variances in the pixel domain must be estimated. To do that, we propose the joint neighborhood median absolute deviation (JNMAD) estimator, which makes the denoising algorithm able to be used in the cases of SNS-AWGNs. The experimental results show that the doubly local Wiener filtering method with block-adaptive windows is superior to other wavelet-based methods using two-dimensional separable wavelet transforms in the case of stationary noise and provides satisfactory performance in the cases of SNS-AWGNs.

A novel unitary PARAFAC method for DOD and DOA estimation in bistatic MIMO radar

The proposed unitary parallel factor (U-PARAFAC) algorithm is based on tensor decomposition.The real-valued tensor signal model still follows a PARAFAC model.Traditional unitary ESPRIT method is firstly extended to the real-valued PARAFAC model.The proposed U-PARAFAC algorithm directly operates the real-valued loading factors instead of estimating the signal subspace. In this paper, a novel unitary parallel factor (U-PARAFAC) algorithm of estimating direction-of-departure (DOD) and direction-of-arrival (DOA) in bistatic multiple-input multiple-output (MIMO) radar is proposed. A real-valued tensor signal model is constructed by applying the traditional forward-backward averaging technique. Subsequently, the fact that the real-valued tensor follows a PARAFAC model is proved, thus the subspace-based high-order singular value decomposition (HOSVD) method can be avoided in the subsequent solving process. Furthermore, directly operating the real-valued loading factors instead of the signal subspace, traditional unitary ESPRIT (U-ESPRIT) method is firstly extended to the real-valued PARAFAC model. The new algorithm, which exploits the multidimensional structure and does not require the estimation of signal subspace, having good performance especially at low signal-to-noise ratio (SNR). More attractively, compared with classical tensor methods such as the PARAFAC algorithm and the unitary tensor-ESPRIT algorithm, the U-PARAFAC algorithm still performs well without sacrificing array aperture when targets are highly correlated or closely spaced. Additional angle pair-matching is not required. Simulation results verify the effectiveness of the proposed algorithm.

Correlated LFM Waveform Set Design for MIMO Radar Transmit Beampattern

Multiple-input multiple-output radar has many advantages over the phased-array radar system due to the waveform diversity, one of which is the greater flexibility to design the transmit beampattern. Hence, waveform set design for transmit beampattern has become an attractive topic, and many methods have been proposed in recent years. However, previous methods cannot synthesize the waveforms with constant-envelope and easy-generation properties. In this letter, we propose to design a set of correlated linear frequency modulation (LFM) waveforms to solve this problem. First, the covariance matrix of the LFM waveform set is analyzed, and the formulation of the transmit beampattern is obtained accordingly. Since the transmit beampattern is mainly affected by the frequency steps and initial phases of the LFM waveforms, the correlated LFM waveform set design problems are formulated by optimizing these parameters for different beampatterns. The resulting problems are solved by adopting the constrained nonlinear optimization, and the LFM waveforms are obtained consequently. The designed waveforms have the properties of constant-envelope and easy generation, and can match the desired transmit beampattern properly. Simulation results demonstrate the superiority of our proposed method.

OFDM Chirp Waveform Diversity Design With Correlation Interference Suppression for MIMO Radar

The orthogonal frequency-division multiplexing (OFDM) chirp waveform has attracted much attention due to its high range resolution, low peak-to-average ratio, and large time-bandwidth product. In its application to multiple-input multiple-output radar, the correlation property of multiple OFDM chirp waveforms should be considered primarily for good detection performance. The simulation results show that high sidelobes exist in correlation functions of the conventional waveforms. In this letter, the reason for high correlation sidelobes is explored first, which is the equal subchirp durations and the same subcarrier bandwidth. Second, two new OFDM chirp waveform diversity design schemes are proposed to suppress the correlation interference. Via designing the various subchirp durations or subcarrier bandwidths specially, the high sidelobes are depressed and the correlation property is improved. Both simulation results and comparisons verify the effectiveness of the proposed methods.

Sparse Representation Framework for MIMO Radar Transmit Beampattern Matching Design

In this paper, the problem of transmit beampattern matching design for multiple-input multiple-output (MIMO) radar is addressed within a sparse representation framework. In the proposed method, a new transmit beampattern design scheme, in which only a multirank transmit beamformer (MRTBF) and some existing orthogonal waveforms are needed to synthesize a desired beampattern, is adopted to tackle the beampattern design problem. Based on the new design scheme, the transmit beampattern design problem is first formulated into the sparse representation framework. Then, in the situation that the Fourier basis is adopted, the MRTBF is obtained through solving the sparse representation problem with a constrained convex optimization and a least-square procedure effectively. It is shown that the waveforms obtained from the resulting MRTBF and some existing orthogonal waveforms can guarantee uniform elemental power transmission. Compared with most of the existing methods, the proposed method has comparable performance but lower computational burden. Numerical experiments are performed to verify the effectiveness of the proposed method.

Polarimetric MIMO radar target detection

Polarimetric Multiple-Input Multiple-Output (MIMO) radar has multiple antennas of different polarimetric directions to transmit and receive signals. For signals in four transmit/receive polarimetric channels, the detection performance is studied via three target detection algorithms, i.e., the Bayesian optimal detection, the coherent accumulation detector and the noncoherent accumulation detector, on conditions that radar targets are anisotropy and two cross polarimetric channels have target returns with different amplitudes. It is found that polarimetric MIMO radar is more stable in target detection performance.

New beamformer for coherent signal reception in the presence of uncorrelated interferences

In this paper, a new beamformer is proposed for coherent signal reception with the assumption that the directions-of-arrival (DOAs) of the uncorrelated interferers are available. Here, the composite vector of the coherent sources is first estimated based on the use of a transformation matrix to eliminate the uncorrelated interferers. Then the optimum beamforming is performed based on the estimated composite vector and the eigenstructure of the array correlation matrix. Experimental results show that the proposed beamformer achieves the optimum performance and rapidly converges.