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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.