Qinetiq Limited

Mohammed Jahangir

Keith M Ponting

Christopher Paul Moate

Paul Graham Kealey

Robert David Hill

The present invention relates to a system and method for processing imagery, such as may be derived from a coherent imaging system e.g. a synthetic aperture radar (SAR). The system processes sequences of SAR images of a region taken in at least two different passes and generates Coherent Change Detection (CCD) base images from corresponding images of each pass. A reference image is formed from one or more of the CCD base images images, and an incoherent change detection image formed by comparison between a given CCD base image and the reference image. The technique is able to detect targets from tracks left in soft ground, or from shadow areas caused by vehicles, and so does not rely on a reflection directly from the target itself. The technique may be implemented on data recorded in real time, or may be done in post-processing on a suitable computer system.

System and method for processing radar imagery

A method of processing a temporal sequence of base images from a synthetic aperture system such as a synthetic aperture radar is provided that simplifies the task of identifying moving objects. The method comprises the steps of firstly temporally filtering a plurality of the base images to form a reference image, and secondly normalising the reference image with a base image to form a change detection image. The change detection image has the property that all moving objects are emphasised. Further processing can optionally be performed on the change detection image to remove false targets based on characteristics of the highlighted areas or on a temporal track taken over a plurality of change detection images. The invention allows detection of moving objects without requiring a Doppler return from a target. The invention extends to a system adapted to implement the method, and a computer program.

System and method for processing imagery from synthetic aperture systems

A method of recognizing a radar target comprises producing a sequence of Doppler spectra of radar returns form a scene and producing therefrom a sequence of Doppler feature vectors for a target in the scene. Hidden Markov modelling (HMM) is then used to identify the sequence of Doppler feature vectors as indicating a member of a particular class of targets. HMM is used to identify the sequence of Doppler feature vectors by assigning to each feature vector an occurrence probability by selecting a probability distribution or state from a set thereof associated with a class of targets, multiplying the occurrence probabilities together to obtain an overall probability, repeating for other probability distributions in the set to determine a combination of probability distributions giving highest overall probability for that class of target, then repeating for at least one other class of targets and selecting the target class as being that which yields the highest overall occurrence probability.

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Birmingham, United Kingdom

Mohammed Jahangir