Liao Guisheng

An estimation method for InSAR interferometric phase combined with image auto-coregistration

In this paper we propose a method to estimate the InSAR interferometric phase of the steep terrain based on the terrain model of local plane by using the joint subspace projection technique proposed in our previous paper. The method takes advantage of the coherence information of neighboring pixel pairs to auto-coregister the SAR images and employs the projection of the joint signal subspace onto the corresponding joint noise subspace to estimate the terrain interferometric phase. The method can auto-coregister the SAR images and reduce the interferometric phase noise simultaneously. Theoretical analysis and computer simulation results show that the method can provide accurate estimate of the interferometric phase (interferogram) of very steep terrain even if the coregistration error reaches one pixel. The effectiveness of the method is verified via simulated data and real data.

Review of reduced rank space-time adaptive processing for airborne radar

This paper overviews reduced rank space-time adaptive processing (STAP) for clutter suppression in airborne early warning (AEW) radars. A new hybrid low dimensional STAP (HSTAP) approach without high implementation cost is also discussed by assigning reasonably the number of system degrees of freedom (DOFs) between the spatial and temporal domains. The clutter rejection performance of the HSTAP method is superior to conventional cascaded space-time processing (CST), which is verified by computer simulations.

Jointly estimating both range and DOA of near field source

A computationally efficient method for jointly estimating both Directions Of Arrival (DOA) and ranges of near field sources is presented. The proposed algorithm does not need any spectral peak searching and the 2-D parameters are automatically paired. It is suitable for arbitrary additive Gaussian noise environment. Furthermore, its performances are confirmed by computer simulations.A computationally efficient method for jointly estimating both Directions Of Arrival (DOA) and ranges of near field sources is presented. The proposed algorithm does not need any spectral peak searching and the 2-D parameters are automatically paired. It is suitable for arbitrary additive Gaussian noise environment. Furthermore, its performances are confirmed by computer simulations.

Fast music spectrum peak search VIA Metropolis-Hastings sampler

A fast MUltiple SIgnal Classification (MUSIC) spectrum peak search algorithm is devised, which regards the power of the MUSIC spectrum function as target distribution up to a constant of proportionality, and uses Metropolis-Hastings (MH) sampler, one of the most popular Markov Chain Monte Carlo (MCMC) techniques, to sample from it. The proposed method reduces greatly the tremendous computation and storage costs in conventional MUSIC techniques i.e., about two and four orders of magnitude in computation and storage costs under the conditions of the experiment in the paper respectively.

A method of designing irregular subarray architectures for partially adaptive processing

A method of dividing a uniform linear array with identical elements into unequally sized subarrays is proposed based on the principle of designing a density tapering array. Noise power at every subarray output is normalized for partially adaptive processing to obtain near-optimum interference suppression performance with low sidelobe level and distortionless mainlobe in the adapted antenna pattern. Unlike regular subarray architectures, irregular subarray architectures may not have a problem with grating lobes. An example of space-time adaptive processing (STAP) for airborne radar systems based on irregular subarrays is given.

A robust adaptive Capon beamforming

Adaptive beamforming suffers from performance degradation in the presence of mismatch between the actual and presumed array steering vector of the desired signal. We propose a novel approach to adaptive beamforming that is robust to array errors. The proposed method involves two steps: the first step is to estimate the actual steering vector of the desired signal, and the second is to obtain optimal weight by utilizing the estimated steering vector. Our method belongs to the class of diagonal loading, but the optimal amount of diagonal loading level can be precisely calculated based on the uncertainty set of the steering vector. Moreover, the proposed robust Capon beamforming has an explicit closed-form solution. Computer simulation results demonstrate its excellent performance. r 2005 Elsevier B.V. All rights reserved.

Evaluation of adaptive space-time processing for inclined sideways looking array airborne radars

This paper evaluates the performance of partial adaptive space-time adaptive processing (STAP) approaches based on Doppler prefiltering for inclined sideways looking array (ISLA) airborne radar, in which the angle between the axis of a linear antenna array with that of platform flight is not zero. In ISLA the STAP is more complex than that in a sideways looking array (SLA), which is the particular case that these two axes are identical. After analyzing the characteristics of the clutter spectrum in ISLA, the principle of reduced rank STAP based on prefiltering is proposed and discussed. Also, several computer simulations are presented.

Recursive algorithm of adaptive weight extraction of space-time signal processing for airborne radars

The non-stationary characteristic of clutter echoes is analyzed in the clutter circumstance of airborne early warning (AEW) radar. A newly 2-D (two dimension) space-time adaptive processing is presented, which is segmented in the range. The segmentation method is determined by analyzing the range of neighboring clutter subspaces. A recursive algorithm of adaptive weight is presented with considering the real-time implementation and the performance of the processor simultaneously. Theoretical analysis and computer simulation results show that the proposed approach is effective.

Sum-difference Reduced-dimensional Processing in SAR Image Domain and Statistical Analysis for Ground Moving Target Indication

In this article, a new reduced-dimensional adaptive processing algorithm based on joint pixels sum-difference data for clutter rejection is proposed. The sum-difference data are obtained by orthogonal projection of the joint pixels data of different synthetic aperture radar (SAR) images generated by a multi-satellite radar system. In the sense of statistical expectation, the sum-differ- ence data contain the common and different information of the SAR images. Therefore, the objective of clutter cancellation can be achieved by adaptive processing. Moreover, based on the residual image after clutter rejection, statistical analysis of constant false-alarm rate (CFAR) detection of moving targets is also presented. Simulation results demonstrate the effectiveness and robustness of the proposed algorithm even with heterogeneous clutter and image co-registration error.

A novel space-borne antenna anti-jamming technique based on immunity genetic algorithm-maximum likelihood

A novel space-borne antenna nulling method is presented on rejecting strong multi-interference from the ground and air. Immune Genetic Algorithm for searching for the multi-extremum of maximum likelihood function has been developed, which is based on injecting vaccine pick-up adaptively. GA has the capability of the whole searching and is not limited by the selection of initial parameter. And the Immune algorithm possesses the advantage of availing oneself of characteristic information. The proposed method, combining GA with the Immune algorithm, can converge at the global optimum quickly and offer high resolution null point. Simulation examples, based on the spot survey data, are shown to illustrate the effectiveness and robustness of the proposed algorithm.