Research On Knowledge-aided Radar Clutter And Interference Suppression Method Using Space-time Adaptive Processing Technology

As a new concept of radar,cognitive radar system is developed from traditional reception-launched open-loop mode to the closed-loop mode, so that, its performance can be improved all-round. Knowledge-aided and adaptive signal processing technologies are the two core modules of cognitive radar system, in which the knowledge-aided technology plays a decisive role in improving clutter suppression ability of cognitive radar. In the real environment, clutters are generally non-homogenous and the statistical properties of different samples are not in the same. Insufficient number of independent and identically distributed samples lead to the performance of suppressing clutter and interference severely degraded using the traditional space-time adaptive processing algorithms. Therefore, we focus on knowledge-aided technology and primarily study the method of suppressing the non-homogenous clutter and interference in cognitive radar receiving end. This paper carries out the following work:(1) By analyzing the working principle of the existing airborne pulse Doppler radar and phased array radar, we study the architecture of cognitive airborne radar system and analyze the advantages of cognitive radar, then we summarize the key technologies in cognitive radar system.(2) We propose a method based on terrain factor to improve the performance of suppressing clutter in a non-homogeneous environment. Firstly, we use the real digital elevation model(DEM) data to establish a non-homogenous airborne radar clutter environment. Secondly, we extract terrain factors from the DEM. Then, we propose a method based on single terrain factor, which uses correlation coefficient as a measure, and select homogenous samples to improve the performance of suppressing clutter in the non-homogeneous environment. In order to verify the effectiveness and feasibility of the proposed algorithm, we use real DEM data to conduct a simulation. The simulation results show that the method, which based on the four terrain factors: the surface roughness, terrain relief, slope and DEM variation coefficient, has better performance than other sample selection methods on suppressing clutter.(3) Since the sample selection method based on different terrain factor has their own strength, so we integrate the four terrain factors and propose a method based on multi-terrain factors to select homogenous samples in the further. Then, we combine this method with knowledge-aided non-homogenous detector(KANHD) which is used to reject interference, as a result, we build a new knowledge-aided homogeneous sample selection method which improves the effects of suppressing clutter and interference. Simulation results show that the new method can suppress cutter and interference in the same time, and it has a good prospect in the cognitive radar.