In this paper, a novel coherent integration algorithm, i.e., two-dimensional frequency domain secondorder keystone transform (FDSOKT), is proposed to detect a weak maneuvering target based on bistatic radar configuration. To eliminate range migration and Doppler frequency migration, the radar echoes are transformed into two-dimensional frequency domain firstly, and then a series of rescaling transforms, matched filter functions and compensation functions are performed respectively. With the elimination of the couplings between range frequency and azimuth frequency caused by radial velocity and acceleration, the energy of the echoes is focused in twodimensional time domain, which improves the detection performance of weak target. In addition, to deal with Doppler ambiguity, different Doppler ambiguity cases are discussed and could be solved well. At last, some simulation experiments are provided and the effectiveness of FDSOKT is proved by the results.

The detection performance of weak target on sea is affected by the special effects of sea clutter amplitude. Aiming at the time and space correlated of sea clutter, the correlated K-distribution sea clutter model is established by the sphere invariant random process algorithm. To solve the problems of range migration (RM) and Doppler frequency migration (DFM) of moving target in the case of long-time coherent accumulation, a novel integration detection algorithm, improved axis rotation short-time Fourier transform (IAR-STFT) is proposed in this paper, which is based on a generalization of traditional Fourier transform (FT) algorithm and combined with improved axis rotation. IAR-STFT not only can eliminate the RM effect by searching for the target motion parameters, but also can divide the non-stationary echo signal without range migration into several blocks. Each block of signal can be regarded as a stationary signal without DFM and FFT is performed on each signal separately. The signals of each block are accumulated to detect the target in the background of the above sea clutter. Finally, the effectiveness of the algorithm is verified by simulation. The results show that the detection ability of this algorithm is better than that of Radon-fractional Fourier transform, generalized Radon Fourier transform and Radon-Lv's distribution in low SNR environment, e.g., when the SNR is -45 dB, the detection ability of this algorithm is about 55%, which is higher than that of Radon-fractional Fourier transform, generalized Radon Fourier transform and Radon-Lv's distribution.