Cognitive Imaging For Through-the-wall Radar

Through-the-Wall Radar(TWR) can detect concealed targets by penetrating walls and other obstacles. Due to the presence of the wall, the moving targets behind the wall facing low signal-clutter ratio(SCR), low signal-noise ratio(SNR) and ghosting, which results in that traditional TWR imaging processing methods are difficult to obtain the desired results. To improve the TWR detection capability and focusing effect of moving targets behind the wall, while weakening ghosting, this paper studies the application of cognitive imaging techniques in stepped frequency ultra wide band(UWB) multiple input multiple output(MIMO) TWR, the main work is as follows:1. To solve the lagging, defocusing and ghosting of moving tagarts behind wall detecting in traditional TWR imaging processing, the cognitive imaging processing framework is proposed based on the theory of cognitive radar.2. An extended TWR imaging model is established to address the problems of environmental parameters estimation when the positional relationship between the wall and the array is unknown.3. Based on the extended TWR imaging model, a compensation imaging method under wall coordinates is proposed to obtain high positioning accuracy and focusing quality radar images.4. A transmit signal power allocation model of power function is proposed via the SCR curve, which can improve SCR and weaken ghosting. Then for the non-adjustable TWR systems, the frequency domain amplitude weighted method is established to simulate waveform adjusting.The TWR cognitive imaging algorithm proposed in this paper are verified by the simulation and actual TWR measured data.