Dynamic Programming Solution for Detecting Dim Moving Targets Part II: Analysis

An on-board mosaic sensor is staring down from a satellite to afixed point on the ground while collecting frames that contain targetsignatures and background noise. A dynamic programmingalgorithm (DPA) has been developed to optimally detect dim movingtargets that cross the sensor's field of view. The algorithm has beendescribed in Part I of this paper. Here, in Part II, we analyze thealgorithm performance and compare it with that of a simpleassembling of thresholded frames; the DPA's SNR performance isshown to be at least an order of magnitude better.     

Application of velocity filtering to optical-flow passive ranging

The performance of the velocity filtering method as applied to optical-flow passive ranging under real-world conditions is evaluated. The theory of the 3-D Fourier transform as applied to constant-speed moving points is reviewed, and the space-domain shift-and-add algorithm is derived from the general 3-D matched filtering formulation. The constant-speed algorithm is then modified to fit the actual speed encountered in the optical flow application, and the passband of that filter is found in terms of depth (sensor/object distance) so as to cover any given range of depths. Two algorithmic solutions for the problems associated with pixel interpolation and object expansion are developed, and experimental results are presented     

Obstacle detection by recognizing binary expansion patterns

A technique is described for obstacle detection, based on the expansion of the image-plane projection of a textured object, as its distance from the sensor decreases. Information is conveyed by vectors whose components represent first-order temporal and spatial derivatives of the image intensity, which are related to the time to collision through the local divergence. Such vectors may be characterized as patterns corresponding to “safe” or “dangerous” situations. We show that the essential information is conveyed by single-bit vector components, representing the signs of the relevant derivatives. We use two recently developed, high capacity classifiers, employing neural learning techniques, to recognize the imminence of collision from such patterns     

Dynamic Programming Solution for Detecting Dim Moving Targets

An on-board scanning or mosaic sensor is staring down from a satellite to a fixed ground point while producing a set of frames that contain target and background signals. Detecting dim moving targets should ideally be done by exhaustively searching over all in he maery(mached fltering), as ppoed possible trajectories in the imagery (matched filtering) as opposed to assembling trajectories from thresholded frames. The dynamic programming approach equivalently substitutes the above prohibitive exhaustive search by a feasible algorithm.     

Error analysis of combined optical-flow and stereo passive ranging

Optical-flow ranging in which the stream of two-dimensional images obtained from a forward-looking forward-moving passive sensor is used to compute range to points in the field of view, and triangulation based on stereo images obtained from at least two stationary sensors are combined. The potential accuracies of the combined optical flow and stereo passive-ranging system are analyzed in the context of helicopter nap-of-the-earth obstacle avoidance. The Cramer-Rao lower bound (CRLB) is developed for the combined system under the assumption of a random angular misalignment common to both cameras of a stereo pair. It is shown that the range accuracy degradations caused by misalignment are negligible compared to those for a monocular optical-flow system