De-noising by wiener filter and wavelet based methods for emitter localization systems

摘要

The Cross Ambiguity Function (CAF) used in signal location estimation is a 2-dimensional complex-valued function of TDOA and FDOA. In TDOA/FDOA systems, pairs of sensors share data to compute the CAF. In practice, the received signals are noisy and this noise perturbs the CAF from its ideal shape which is a big main lobe and some small side lobes. At low SNRs, the CAF main lobe is buried in the noise and the location estimation accuracy is poor. In this paper, by exploiting some of the CAF properties, we de-noise the CAF itself to increase the estimation performance. We use Wiener filter and wavelet based methods for de-noising. The impact of such de-noising methods on the overall location accuracy is assessed via simulations.