Adaptive spectral conditioning for improved radar detection

In moving target radar scenarios temporal nonstationarities can profoundly effect performance of spatial target detectors. These nonstationarities are often ignored simply because it has been computationally inefficient, or mathematically intractable to handle them. This nonstationary noise, however can often be localized in spatial frequency. A spatial multiresolution Markov structure can thus be used to isolate these temporal nonstationarities. In this paper we employ a multiresolution-Markov matched filter detection scheme that integrates Kalman conditioning criteria to remove temporal nonstationarities and thereby improve radar detection performance.