Regional stereo matching algorithm is sensitive to illumination change. Disparity map has the problems that target and the weak texture region mismatch, boundary is not smooth, and so on. In order to solve these problems, an improved quick stereo matching algorithm by using visual saliency characteristics was proposed. Saliency detection was used to locate the main target area in the image. Then feature matching was completed by combining image Sobel edge characteristics and phase features to get the rough disparity map. Finally, by detecting visual saliency in the disparity map, abrupt noise in weak texture image area was eliminated. Compared to the traditional algorithms such as Sum of Absolute Differences (SAD), Sum of Squared Differences (SSD), Normalized Cross Correlation (NCC), the proposed algorithm is not sensitive to light changing, and it can get better disparity map and higher matching rate, which is conducive to real-time applications.

In view of the characteristics of Ka-band mobile satellite channel, a model was built up with taking full consideration of the decline influenced by weather and surrounding environment in this paper. Then, the satellite channel with Bipolarity Phase Shift Keying (BPSK) modulation was simulated, and the probability model of baseband channel bit error distribution was established. Meanwhile, the probability of error occurrences was fitted by using the least-squares method. According to the results, the occurrence number of channel errors obeys Poisson distribution. Moreover, during the digital baseband simulation of Ka-band mobile satellite channels, it is found that the system error with BPSK modulation consists of the burst error and the random error that obeys the Poisson distribution.