Linjian Zhang

Robust Channel Phase Error Calibration Algorithm for Multichannel High-Resolution and Wide-Swath SAR Imaging

High-resolution and wide-swath synthetic aperture radar (SAR) imaging can be achieved by the azimuth multichannel system. The minimum variance distortionless response (MVDR) beamformer can be utilized to suppress azimuth ambiguities. However, the presence of channel phase errors significantly deteriorates the performance of the azimuth multichannel SAR system. Instead of employing subspace techniques, this letter proposes a robust channel phase error calibration algorithm via maximizing the MVDR beamformer output power. Compared with the conventional subspace-based calibration methods, there is no redundancy of channels required to estimate the subspaces in the proposed algorithm. Also, the proposed algorithm is relatively robust, because it avoids the subspace swap phenomenon, which probably takes place at low signal-to-noise ratios for the subspace techniques. Moreover, the proposed method has the advantage of estimating the channel phase errors without covariance matrix decomposition, which reduces the computation load. The simulation experiments and the real data processing validate the effectiveness of the proposed calibration method.

Azimuth wavefront modulation using plasma lens array for microwave staring imaging

Microwave staring imaging scheme based on range pulse compression and azimuth wavefront modulation is a new radar scheme. Under the condition of no relative motion between radar and scene, the scheme can obtain radar images with high resolution in both range direction and azimuth direction. The paper presents this imaging technique by theoretical analysis and simulation. Microwave staring imaging structure is introduced firstly. Then, requirement of the azimuth wavefront modulation and target change detection is analyzed.

A novel method for estimating the baseband Doppler centroid of conventional synthetic aperture radar

The Doppler centroid is a crucial parameter for the purpose of implementing azimuth processing for synthetic aperture radar (SAR) data. In this paper, we propose a scheme for estimating the Doppler centroid of conventional SAR. Virtual multi-channel SAR data can be generated by sub-sampling the original SAR data in azimuth. Consequently, each channel data is aliased and the spectrum components within each Doppler bin can be viewed as sources from different known directions. Then the Capon spectral estimator can be utilized to estimate the antenna pattern. Based on the estimated antenna pattern, we can obtain the baseband Doppler centroid of the original SAR data. Finally, experiments are provided to validate the effectiveness of the proposed algorithm.

A blind reconstruction of azimuth signal for multichannel HRWS SAR system

Uniformly spaced multichannel system makes it available to achieve the high-resolution and wide-swath (HRWS) synthetic aperture radar (SAR) images. Exact knowledge of the steering vectors is required to reconstruct the azimuth signal. The steering vectors depend upon the pulse repetition frequency (PRF), the platform velocity and the spacing between two adjacent channels. However, the errors existing in these parameters lead to the deterioration of ambiguity suppression. This paper proposes a method to estimate these parameters and obtain the relatively accurate steering vectors. The proposed method exploits the rotational invariance between two signal subspaces. Consequently, a blind reconstruction of azimuth signal can be implemented without knowing the aforementioned parameters. Then we perform experiments based on simulations and real data processing to verify the effectiveness of the proposed method.

A subspace algorithm of calibrating channel gain and phase errors for HRWS SAR imaging

Azimuth multichannel SAR system is a promising solution to achieve high-resolution and wide-swath (HRWS) imaging for spaceborne synthetic aperture radar (SAR) system. These spectrum components within a Doppler bin can be considered as virtual signal sources from different known directions. Thus the azimuth signal of multichannel SAR can be reconstructed via digital beamforming (DBF) techniques. However, the performance of restoring Doppler full spectrum degrades significantly due to the existence of channel gain and phase errors in azimuth multichannel SAR system. In this paper, a subspace calibration algorithm is proposed for the HRWS SAR imaging system. The fundamental idea behind the proposed algorithm is that the signal subspace is equivalent to the space spanned by the practical steering vectors of the multichannel SAR system. Moreover, we discuss the uniqueness of the calibration of the proposed method. Finally, real airborne multichannel SAR data processing demonstrates that the proposed method can effectively and excellently calibrate the channel gain and phase errors.

Fast channel phase error calibration algorithm for azimuth multichannel high-resolution and wide-swath synthetic aperture radar imaging system

Abstract. The configuration of multiple uniformly spaced channels in azimuth can achieve high-resolution and wide-swath images for synthetic aperture radar (SAR) systems. The unambiguous Doppler spectrum can be reconstructed via digital beamforming (DBF) techniques in the azimuth multichannel SAR system. However, the performance of DBF deteriorates significantly because of the inevitable channel errors in practical applications. Since the SAR antennas are generally unweighted in azimuth, the power of the SAR signal is symmetrically distributed around the Doppler centroid in the azimuth frequency domain. Based on this observation, the covariance matrix of multichannel output in the range-Doppler domain can be regarded as a real matrix when there is no existence of channel errors and the correction of the baseband Doppler centroid is applied. Consequently, we propose a fast calibration algorithm to calculate channel phase errors. The proposed method can acquire the estimation of phase errors directly from the covariance matrix. Thus, the proposed method has the properties of high robustness and low computation load. Theoretical analysis and experiments validate the performance and the efficiency of the proposed algorithm.

System design of optronic processing for azimuth signal reconstruction in HRWS SAR based on filterbank framework

With the high programmability of spatial light modulator (SLM), an optronic processor which is capable of processing synthetic aperture radar (SAR) raw data in real time is newly developed. Azimuth signal reconstruction is an essential problem with regarding to high-resolution wide-swath (HRWS) SAR, which is always time consuming. This paper proposes an optronic system for reconstructing azimuth signal of HRWS SAR. In the optronic system, the major computation is performed by optical devices, whereas electronic devices control the data. This system can be a promising solution to azimuth reconstruction of spaceborne HRWS SAR.

Reconstruction of azimuth signal for multichannel HRWS SAR imaging based on periodic extension

Along a roughly chronological order, the azimuth signals undersampled from the multichannel synthetic aperture radar (SAR) for high-resolution wide-swath (HRWS) imaging correspond to recurrent nonuniform sampling. Only a finite-duration sequence of samples of the azimuth signal can be obtained in practical applications. A new recurrent nonuniform sampling scheme can be generated by extending these samples periodically across the boundaries provided that the azimuth signal is bandlimited. Thus, from the perspective of reconstructing recurrent nonuniform sampling, an innovative reconstruction algorithm for suppressing azimuth ambiguities of multichannel HRWS SAR is proposed, which is suitable to be implemented on digital computers. Furthermore, the presented algorithm acquires the filter weights without matrix inversion reducing tremendously the computational load.

Azimuth signal reconstruction for HRWS SAR from recurrent nonuniform samples

The azimuth signal undersampled from the multi-channel SAR system for high resolution and wide swath imaging can be considerded as recurrent nonuniform sampling, which is a special case of multichannel sampling. Then from the point of view of reconstructing a bandlimited signal from recurrent nonuniform samples, we propose an new reconstruction algorithm based on filter-bank framework for suppressing azimuth ambiguities and therefore restoring the unambiguous azimuth full spectrum. The proposed algorithm has the advantage of acquiring the filter weights without matrix inversion over other reconstruction algorithms, which reduces tremendously the computation load. Finally, the performance of our algorithm is validated by numerical experiments.