ADAPTIVE LATTICE FILTERING FOR RADAR APPLICATIONS

This thesis examines the lattice-structure prediction-error filter, and its application to air-traffic-control radar for the detection of targets (such as aircraft) obscured by clutter (unwanted reflections from the ground or weather systems). The digitally implemented lattice-structure filter adapts to and eliminates the clutter spectrum, producing an output only when a target causes a change in the input signal. Conventional MTI filters do not perform this detection as reliably.;The adaptive learning characteristics (both stationary and non-stationary) of these lattice methods were studied theoretically and experimentally, and quantitative relationships were developed describing their behaviour. The performance of the lattice-structure as a radar clutter filter was examined in terms of improvement factor, receiver-operator-characteristic, and sub-clutter visibility. Both simulated and actual radar data were used. The actual radar data included signals from aircraft, bird flocks, ground clutter, and several types of weather clutter. The performance of the lattice-structure filter with this data was found to be more consistent and consistently better than the conventional MTI filter.;Adaptation to an input signal results from the recursive calculation of the lattice-structure filter's reflection coefficients. Six algorithms for this calculation were examined and compared using simulated radar data. A number of adaptive methods for continuously implementing these algorithms were also analysed. These included the standard gradient and least-squares methods, and two new methods developed in this thesis, the simple gradient and adaptive gradient methods. The harmonic-mean algorithm and the standard simple gradient methods were selected as most appropriate for this application.