| Dynamic-state estimation for terrain-ranging image-mapping systems rigidly attached to a moving vehicle can be used to provide a good data base for accurate and reliable positional estimates such as relative terrain range, altitude and direction. The positional estimation, in turn, can readily be used for the vehicle control of cruising, pointing, or terminal homing.; A simple recursive algorithm for continuous dynamic-positional-state estimation referenced to a moving vehicle equipped with the above image-mapping systems is developed by making use of optimal and suboptimal Kalman filters and minimization techniques of the least squares loss function subject to constraints of budget, simplicity and survivability in hostile environment. The applied theories are mainly the theories of system and optimal control with some broad understanding of navigation and electro-optics.; The general objectives of the algorithm are to make selected measurements of the outputs of the image-mapping systems to minimize the trace of the resulting error covariance matrix of the state estimates and also to make selections such that the error covariances of the estimates of unmeasured quantities be small. A performance index for use in the algorithm is developed and evaluated. |
