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The study develops an algorithm to improve coherence for the multichannel airborne along-track synthetic aperture radar (SAR), which can be used for ground moving target indication (GMTI) by comparing two SAR images obtained from different channels. The turbulent aircraft motion, beam pattern difference and frequency response difference that may degrade the coherence are discussed in detail. The aircraft motion error is firstly estimated and corrected based on the range compressed data. After focusing on the beam pattern differences and the receive channel imbalance are compensated using the two two-dimensional (2-D) adaptive filters, the first in the range-Doppler domain and the second in the range-frequency azimuth-time domain. It is shown that using the coherence improving algorithm the coherence of SAR complex image pairs can be improved greatly. The effectiveness of the algorithm is demonstrated with real data acquired by a Chinese X-band multichannel airborne SAR-GMTI system.

Ground moving target indication (GMTI) is one of the most important applications of the bistatic synthetic aperture radar (SAR) system as well as the monostatic system. An algorithm for moving target detection and location is presented with an azimuth-invariant bistatic multichannel SAR, which consists of one transmitter (channel) and multireceivers (multichannel). The algorithm is based on the discussion of the particularities of the bistatic SAR configuration including coherence improvement and clutter characteristics. Then, the corresponding compensating methods including two-dimensional range-azimuth prefiltering and bistatic differential range correction are proposed to solve these particularities. It is shown that using the compensating methods, the stationary clutter can be suppressed and the moving parameters of ground targets can be estimated accurately. Finally, simulation results demonstrate the effectiveness of the proposed algorithm.

Intense co-channel interference (CCI) severely depresses the target detection in high-frequency surface wave radar (HFSWR). In this study, the CCI cancellation algorithm by time and range adaptive processing is proposed for a novel HFSWR - bistatic HF surface wave synthesis impulse and aperture radar. With the real data, the interference is firstly modelled and then its features are investigated. The analyses show that the same interference prevails over a few but different bins through different channels, whereas the echoes are relatively weak and exist in all bins; in range domain, however, the interference takes over all the bins including positive and negative bins and will spread over the same and considerable Doppler area through different channels, whereas the echoes appear only in partially positive bins. On the basis of the features, the interference covariance matrix can be obtained by selecting the samples whose average power is much higher than that of the others in time domain and in range domain; the samples from either or both of beyond the detectable bins and negative bins can be selected for training. The interference can be cancelled by projecting the polluted data into the orthogonal subspace, constructing the projecting matrix with the eigenvectors associated with large eigenvalues of the covariance matrix. Finally, the segment handling and samples requirement are also discussed for reducing the computation burden. The experimental results are provided to demonstrate the performance of the method.