Study Of Adaptive Waveform Sslection Algorithm Based On Broadband Cognitive Radar

Appearance of broadband Cognitive radar is due to the intelligence of radar. Comparing to traditional radar, Cognitive radar could change the waveform along to the variety of target and surroundings.The flexibilities and self-adaptation make Cognitive radar become research hotspots in the field of modern radar,and gets a lot of attention from any aspects.Cognitive,learning and recording the state of surroundings and targets,is the foundation for Cognitive radar. Self-adaptive algorithm is the core of Cognitive radar,which can change the waveform after getting the state of su rroundings and targets.The thesis nd pay more attention to the self-adaptive ability. Thesis carried out the flowing tasks:1.Researched the clutter surroundings and established the clutter model which can describe the state of clutter surroundings.Then we researched the self-adaptive waveform selection theory,including dynamic programming theory and self-adaptive waveform selection model.2. Thesis analyzed the performance of classic target detection algorithms and the target detection algorithm based on sample information cumulative. Then we researched self-adaptive waveform selection algorithm based on dynamic programming theory.we researched value-iteration algorithm, improved value-iteration algorithm, Q-Learning algorithm. Finally we researched Q-Learning algorithm with self-adaptive iteration Step-length.Also we contrast the percent of accuracy of different algorithm based on the emulation analysis.3.According to the demand of Low Probability of Intercept(LPI) to radar waveform,this thesis researched self-adaptive waveform optimization algorithm with Low Probability of Intercept(LPI).We found the factors influencing the performance of LPI,and optimized the performance of LPI through compound modulation, extending the coding length of signal.Finally,we prove the effectivity of the algorithm by analysing emulation result.4. According to the demand of aid knowledge for Cognitive radar,we researched waveform design algorithm based on self-adaptive waveform parameter.The algorithm optimize the next waveform parameter by using echo information of the front waveform.After analysing,we found the relationship between SINR and Phase vectors.Finally,we contrast the difference of detection performance between optimized signal and unoptimized.