Jiangbo Liu

Source Association, DOA, and Fading Coefficients Estimation for Multipath Signals

This paper addresses the source association (SA), direction of arrival (DOA), and fading coefficients (FCs) estimation problem in multipath environment. First, we establish a rank reduction property for a multipath signal model with the existence of multiple groups of coherent signals. Subsequently, based on this property, effective algorithms for SA, DOA, and FCs estimation have been developed. The proposed DOA and FCs estimation methods exploit the multipath structure information to achieve improved accuracy. The new DOA estimation methods work well even in the case that the DOAs of the multipath signals associated with different sources are (nearly) overlapped. Meanwhile, the new methods are applicable to arbitrary array geometry while without decreasing the effective array aperture. Then, the stochastic Cramér–Rao bound on DOA and FCs estimation of multipath model (MCRB) exploiting the multipath structure information is derived in closed form. Numerical simulations have been provided to demonstrate the effectiveness of the proposed methods.

DOA and Gain-Phase Errors Estimation for Noncircular Sources With Central Symmetric Array

The problem of direction-of-arrival (DOA) estimation for noncircular sources impinging on a central symmetric array (CSA) in the presence of sensor gain-phase uncertainties is addressed in this paper. A noniterative method is proposed and the corresponding stochastic Cramér–Rao bound is derived. The proposed method is realized through two steps. First, an eigenstructure-based technique is presented to estimate the spatial signatures. Second, the DOAs are obtained by adopting an element-wise division approach to the estimated spatial signatures, based on which, the sensor gain-phase errors are given in closed-form. The ambiguity of DOA estimation is analyzed as well. The proposed method offers a number of advantages in comparison with the existing methods that apply to CSA. First, the DOA estimator is independent of the sensor phases. Second, the proposed method applies to incoherent sources. Third, the proposed method is capable of providing 360° azimuthal coverage under certain conditions. Fourth, an additional performance gain is achieved by taking the property of noncircular sources into consideration. Numerical simulations are provided to verify the effectiveness of the proposed method.

Bl-GESPAR: A fast SAR imaging algorithm for phase noise mitigation

The performance of Synthetic aperture radar (SAR) imagery is often significantly deteriorated by the random phase noises arose from the atmospheric turbulence or frequency jitter of the transmit signal within SAR observations. The computational time of the traditional phase retrieval based SAR autofocus algorithms is sharply increased with the size of scene. In this paper, we recast the SAR imaging problem via the phase-corrupted data as a special case of block-based quadratic compressed sensing (BBQCS) problem. We propose a novel fast SAR imaging algorithm to recover the focused well SAR image from the phase-corrupted data and reduce the computational time and memory requirement for several orders of magnitude. Experimental results show our proposed algorithm not only reduces the computational complex but also provides satisfactory reconstruction performance.

Robust adaptive beamforming for noncircular signal against array steering vector mismatch and interference nonstationarity

The performance of adaptive arrays is severely degraded if the weights are in the presence of interference nonstationarity and signal steering vector mismatch. Because of this, we proposed a new robust null broadening adaptive beamforming algorithm. The method is realized by the combination of projection transform and diagonal loading technique. We got a new sample covariance matrix through diagonal loading technique and the received data transform technique which is based on the concept of subspace projection. We applied the proposed algorithm to noncircular signals which are usually encountered in the context of radio communications. According to the theoretical analysis, the projection transform operation can improve the orthogonality between signal subspaces and noise subspaces. The proposed approach can effectively broaden the jammer nulls and strengthen the null depth. Simulation results demonstrate that the proposed algorithm can provide strong robustness against both signal steering vector mismatch and jammer motion.