Underwater terrain-aided navigation is used to complement the traditional inertial navigation employed by autonomous underwater vehicles during lengthy missions. It can provide fixed estimations by matching real-time ...Underwater terrain-aided navigation is used to complement the traditional inertial navigation employed by autonomous underwater vehicles during lengthy missions. It can provide fixed estimations by matching real-time depth data with a digital terrain map, This study presents the concept of using image processing techniques in the underwater terrain matching process. A traditional gray-scale histogram of an image is enriched by incorporation with spatial information in pixels. Edge comer pixels are then defined and used to construct an edge comer histogram, which employs as a template to scan the digital terrain map and estimate the fixes of the vehicle by searching the correlation peak. Simulations are performed to investigate the robustness of the proposed method, particularly in relation to its sensitivity to background noise, the scale of real-time images, and the travel direction of the vehicle. At an image resolution of 1 m2/pixel, the accuracy of localization is more than 10 meters.展开更多
Terrain referenced navigation estimates an aircraft navigation status by utilizing a radar altimeter measuring a distance between the aircraft and terrain elevation. Accurate digital elevation map is essential to esti...Terrain referenced navigation estimates an aircraft navigation status by utilizing a radar altimeter measuring a distance between the aircraft and terrain elevation. Accurate digital elevation map is essential to estimate the aircraft states correctly. However, the elevation map cannot represent the real terrain perfectly and there exists map error between the estimated and the true maps. In this paper, an influence of the map error on measurement equation is analyzed and a technique to incorporate the error in the filter is proposed. The map error is divided into two sources, accuracy error and resolution error. The effectiveness of the suggested technique is verified by simulation results. The method modifies a sensor noise covariance only so there is no additional computational burden from the conventional filter.展开更多
基金Supported by the National Natural Nature Science Foundation of China （Grant No. 41376102）, Fundamental Research Funds for the Central Universities （Gant No. HEUCF150514） and Chinese Scholarship Council （Grant No. 201406680029）.
文摘Underwater terrain-aided navigation is used to complement the traditional inertial navigation employed by autonomous underwater vehicles during lengthy missions. It can provide fixed estimations by matching real-time depth data with a digital terrain map, This study presents the concept of using image processing techniques in the underwater terrain matching process. A traditional gray-scale histogram of an image is enriched by incorporation with spatial information in pixels. Edge comer pixels are then defined and used to construct an edge comer histogram, which employs as a template to scan the digital terrain map and estimate the fixes of the vehicle by searching the correlation peak. Simulations are performed to investigate the robustness of the proposed method, particularly in relation to its sensitivity to background noise, the scale of real-time images, and the travel direction of the vehicle. At an image resolution of 1 m2/pixel, the accuracy of localization is more than 10 meters.
文摘Terrain referenced navigation estimates an aircraft navigation status by utilizing a radar altimeter measuring a distance between the aircraft and terrain elevation. Accurate digital elevation map is essential to estimate the aircraft states correctly. However, the elevation map cannot represent the real terrain perfectly and there exists map error between the estimated and the true maps. In this paper, an influence of the map error on measurement equation is analyzed and a technique to incorporate the error in the filter is proposed. The map error is divided into two sources, accuracy error and resolution error. The effectiveness of the suggested technique is verified by simulation results. The method modifies a sensor noise covariance only so there is no additional computational burden from the conventional filter.
