Detection and estimation with redundant range differences

In this paper, we explore the use of redundant range differences in signal estimation and detection. Redundant range differences are known to lie in a certain subspace. This information forms our basis of estimation and detection algorithms. In addition to this information, we also use the configuration of the base stations to check the consistency of range difference estimates. In summary we propose the shrunken estimator as an improvement over the least squares estimator for range difference smoothing. Shrunken estimator is known to give less mean square error compared to the least squares estimator. For detection purposes we propose an method that can passively detect the presence of a signal form redundant range differences which is based on matched subspace detectors.