| 摘要 |
A method and apparatus are provided for classifying range profiles, generated for example by a radar, lidar or sonar. In the method, each in a set of objects of interest is modelled with a probabilistic model. The probabilistic model represents the probabilities of occurrence of different possible sequences of distances between selected features of the object, in different orientations, that are likely to result in peaks of backscatter in a range profile of the object. The probabilistic model is derived from a first probabilistic representation of each selected feature, generated to represent the uncertainty in locating the feature and the uncertainty in observing the feature in a range profile. Classification is achieved by calculating, for each probabilistic model, the probability that the model would generate a given sequence of distances between observed backscatter events in a given range profile. The model generating the given sequence with the greatest probability identifies the object likely to have produced the given range profile. Preferably, the probabilistic models comprise Hidden Markov Models (HMMs).
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