Low-frequency Ultra-wideband Synthetic Aperture Research Articles

Extended Subaperture Imaging Method for Airborne Low Frequency Ultrawideband SAR Data.

The subaperture processing is one of the essential strategies for low frequency ultrawideband synthetic aperture radar (LF UWB SAR) imaging, especially for the real-time LF UWB SAR imaging because it can improve the parallelization of the imaging algorithm. However, due to the longer synthetic aperture of LF UWB SAR, the traditional subaperture imaging encounters an azimuth ambiguities problem, which severely degrades the focused quality of the imaging results. In this paper, the reason for the presence of azimuth ambiguities in the LF UWB SAR subaperture imaging and its influence on image quality is first analyzed in theory. Then, an extended subaperture imaging method based on the extension of subaperture length before Range Cell Migration Correction (RCMC) was proposed. By lengthening the subaperture length, the azimuth ambiguities are effectively eliminated. Finally, the extended part of subaperture is wiped off before the azimuth compression (AC), and the LF UWB SAR image of high focused quality is obtained. The correctness of the theory analysis and the effectiveness of the proposed method have been validated through simulated and real LF UWB SAR data.

Modified nonlinear chirp scaling algorithm for one-stationary bistatic low frequency ultrawideband synthetic aperture radar imaging

We outline a modified nonlinear chirp scaling algorithm (NLCSA) for one-stationary bistatic synthetic aperture radar (BiSAR) using low-frequency (LF) and an ultrawideband (UWB) signal. The existing NLCSAs for one-stationary BiSAR will be invalidated in an LF and UWB application because the higher-order phase error (HOPE) due to the Taylor series approximation cannot be ignored in this case. We first analyze the effect of the HOPE on bistatic LF UWB SAR imaging theoretically. Then, a modified method based on the higher-order phase compensation (HOPC) and block processing is proposed to deal with the HOPE. Finally, the simulation results demonstrate the correctness of the theory analyses, and the validity of the proposed algorithm is presented.

Performance Evaluation of Frequency-Domain Algorithms for Chirped Low Frequency UWB SAR Data Processing

This paper studies the performance of the frequency-domain algorithms (FDAs) for low-frequency ultra-wideband synthetic aperture radar (UWB SAR) data processing. First, a generalized theoretical derivation of the FDAs is presented from the viewpoint of SAR signal processing. The derivation not only provides a deeper understanding to the imaging principle of the extended Omega-K algorithm (EOKA), but also makes it compatible and comparable with the other FDAs. Second, the performance comparison on different FDAs is made based on theoretical analysis, simulation and experimental data. The comparison results show that the Omega-K algorithm (ωKA) has the highest imaging precision in the ideal case (i.e, no motion error), but its application is limited by the poor ability of compensating motion errors. In contrast, the EOKA and nonlinear chirp scaling algorithm (NCSA) have excellent performance on dealing with the motion error, but they can only be applied under specific preconditions. Besides, as cetner frequency gets lower, the fractional bandwidth and integration angle get larger, the imaging precision of NCSA greatly decreases, while the ωKA and EOKA still keep high precision.

SPARSE TIME-FREQUENCY REPRESENTATION BASED FEATURE EXTRACTION METHOD FOR LANDMINE DISCRIMINATION

Low-frequency ultra-wideband synthetic aperture radar is a promising technology for landmine detection. According to the scattering characteristics of body-of-revolution (BOR) along with azimuth angles, a discriminator based on Bayesian decision rule is proposed, which uses sequential features, i.e., double-hump distance. First, the algorithm estimates the target scatterings in all azimuth angles based on regions of interest. Second, sequential aspect features are extracted by sparse time-frequency representation. Third, the distributions of features are obtained by training samples, and then the posterior probability of landmine class is computed as an input to the classifler adopting Mahalanobis distance. The experimental results indicate that the proposed algorithm is efiective in BOR target discrimination.

Low-frequency ultra-wideband synthetic aperture radar ground moving target imaging

A method for low-frequency ultra-wideband synthetic aperture radar (SAR) imaging of ground moving targets is proposed in this study. This method can deal with large range migration of the moving target. A first-order keystone transform is used to correct range walk (first-order range migration), and range curvature (second-order range migration) is compensated by using a second-order keystone transform. Both the first-order and second-order keystone transform parameters are independent of the motion parameters, so that this method can correct the range migration for all targets without knowing their velocity. The advantage of this method is that it can correct range curvature for all targets in one processing step, so that it is simple to implement. Simulation and experimental SAR data processing results are shown to demonstrate the validity of the proposed method.

RFI suppression in ultra-wideband SAR systems using LMS filters in frequency domain

A least-mean-square algorithm in the frequency domain, with arnplitude normalisation, is proposed to remove narrowband radio frequency interference in low-frequency ultra-wideband synthetic aperture radar systems. The performance of the algorithm was tested on experimental data acquired with the CARABAS system.