Iterative geolocation based on cross-view image registration (IGCIR) for long-range targets

The geolocation of ground targets by airborne image sensors is an important task for unmanned aerial vehicles or surveillance aircraft. This paper proposes an Iterative Geolocation based on Cross-view Image Registration (IGCIR) that can provide real-time target location results with high precision. The proposed method has two key features. First, a cross-view image registration process is introduced, including a projective transformation and a two-stage multi-sensor registration. This process utilizes both gradient information and phase information of cross-view images. This allows the registration process to reach a good balance between matching precision and computational efficiency. By matching the airborne camera view to the preloaded digital map, the geolocation accuracy can reach the accuracy level of the digital map for any ground target appearing in the airborne camera view. Second, the proposed method uses the registration results to perform an iteration process, which compensates for the bias of the strap-down initial navigation module online. Although it is challenging to provide cross-view registration results with high frequency, such an iteration process allows the method to generate real-time, highly accurate location results. The effectiveness of the proposed IGCIR method is verified by a series of flying-test experiments. The results show that the location accuracy of the method can reach 4.18 m (at 10 km standoff distance).