A Deinterleaver Algorithm In Complex Signal Environment

Radar emitter signal deinterleaver is one of the key procedures of signalprocessing in ELectronic INTelligence (ELINT), Electronic Support Measures (ESM) and Radar Warning Receiver (RWR) systems in electronic warfare. It is also the precondition and foundation of electronic interfering.As countermeasure activities in modern electronic warfare become more and more drastic, advanced radars increase rapidly and play an important role in this area. Complex and changeful signal waveform weakens greatly the validity of traditional deinterleaver methods and makes the validity lose gradually. Radar emitter signal deinterleaver has been confronted with many challenges.Aiming at the problem of the traditional deinterleaver methods, a new synthesis deinterleaver algorithm for advanted radar emitter signals are studied systematically and exploringly in this dissertation. The main jobs are as following:1. The high precision measure of radar signal parameters which is the precondition of deinterleaver. Aiming at the error of time parameters, this dissertation introduced a method of precise time measure and designed a circute board to see whether the method was effitive.2. We analysed the characteristics of radar signal based on the purpose of the radar, used the radar's intra-pulse in the new deinterleaver methods.3. We introduced a new algorithm to sort unknown radar signals, which used clustering and multiple hypothese merge methods.Differing from the traditional algorithm which relied on the parameter of PRI, the new method used multidimensional ponderance of the radar. Meanwhile, feature extraction and multiple hypothese merge methods emphasized more on mastering the various patterns of the radar. To design the deinterleaver from the purpose of the radar was beneficial to solve the problem which the traditional method had.4. A method of sorting foregone radar signals was introduced. In face of complex environment, only one radar signal sorting algorithm may not work well, and its result may be fuzzy, even occurring fatal error. In order to solve this problem we used data fusion to deal with the result of other radar signal sorting algorithm, such as Kalman Fliter, Fuzzy Pattern Recognition etc. The new method can adapt to the transformation of the radar patterns or the environment, it has a validity comparing to traditional method of dealing with the foregone radar signal, so the quantity of unknown radar signal is decreased.