Space-surface bistatic synthetic aperture radar (SS-BSAR) has gained more and more researcher's interests. In this paper, we focus on improving range resolutions of GNSS illuminator based SS-BSAR with the method of spectrum synthesis of ultra-wide-band (UWB). Narrow bandwidth signals, such as GPS P code, can be spliced into a wider signal. Simulation results show that it can effectively increase signal processing bandwidth, improve range resolution and target recognition capabilities.

In this paper, we present a new numeric bistatic range migration algorithm (RMA), specifically designed for GPS signal based space-surface bistatic SAR(SS-BSAR). It can be applied to any arbitrary trajectory BSAR imaging system. Based on the principle of stationary phase and the geometric relationship of the SS-BSAR, a two dimensional (2-D) precise analytic response expression of point targets in frequency domain is deduced first. Then a numeric RMA is proposed which match function and interpolation function are derived numerically. The proposed RMA can process wide SAR scene at once and the shape distortion can be corrected at the same time. Simulation results illustrate the validity of the proposed approach.

A low-complexity method for source enumeration is proposed in this letter. Given the training data of a desired signal, an array data matrix is partitioned into orthogonal signal and noise components. The noise components are then used to calculate the total description length required to encode the array data. The model with the minimum description length (MDL) is chosen as the best model. Unlike the traditional MDL methods, the proposed method linearly partitions the array data into the cleaner signal and noise components and thereby is more accurate and computationally efficient. Its performance is demonstrated via numerical results.

A low-complexity ESPRIT method for direction-of-arrival (DOA) estimation is proposed in this paper. Unlike the conventional subspace based methods for DOA estimation, the proposed method only needs the training data of one signal to perform the forward recursions of the multi-stage Wiener filter (MSWF), does not involve the estimate of the covariance matrix or its eigendecomposition. Thus, the proposed method is computationally advantageous. Numerical results are given to illustrate the performance of the proposed method.

A new method is developed to merge two spatially registered images with diverse focus based on multiresolution wavelet decomposition and evolutionary strategy (ES). At first, the wavelet decomposition without down-sampling is used to perform an addition of wavelet high-frequency components of each image. Then, in terms of difference of area-based energy feature in two original images, ES is adopted to partition the region and perform the fusion. The experimental results show that the proposed method can achieve better fusion performance than wavelet transform (WT) method.