The traditional collaborative representation for hyperspectral anomaly target detection algorithm ignores the spatial information of the image and leads to low detection accuracy. Therefore, an Improved Collaborative Algorithm Based on Spatial-spectral Joint Characteristics for Hyperspectral Anomaly Detection algorithm is proposed. The algorithm constructs a certain size space window centered on the pixel to extract spatial information capable of representing the pixel class, and the image block vector of the pixel is obtained. Combining spectral information with spatial information, the concept of spectral collaboration and spatial collaboration is proposed, and weighting the two and obtaining the result of the algorithm. The algorithm is used to simulate the three sets of real hyperspectral data and compared with the existing algorithms, verifying the advancement of the algorithm.