Radar Waveform Design Based On Chaos Theory And Its Applications

With the rapid development of electronic countermeasures,the electromagnetic environment is becoming increasingly complex,and modern radars are facing more and more challenges for survival.Therefore,how to ensure that the radar has good detection performance while possessing low probability of detection,interception and good electromagnetic compatibility has become important concerns of modern radar designers.Noise radar uses random noise as the radar emission waveform,which has natural immunity to other noise interferences,but the truly ideal random noise is not easy to obtain and difficult to reproduce and process,which confines its engineering application.Therefore,pseudorandom signals are commonly used to replace random noise.Chaotic signals have noise-like characteristics;they are a good type of random radar signal source and are easier to generate,reproduce and process than random noise.There is an important theoretical and engineering significance to apply chaos theory to the radar field,and this dissertation mainly focuses on the related prob-lems in chaotic radar systems and the waveform design.The main contributions and innovations are as follows:1.The characteristic difference between random noise and chaotic signal is stud-ied,and a chaotic signal noised algorithm is proposed.Theoretically,chaotic signals are notably suitable for noise radar for their initial value sensitivity,aperiodicity,etc.However,the inherent determinacy of chaotic systems determines that many chaotic signals cannot be directly used as radar waveforms.The chaotic signal noised method is based on the representation of the floating-point number in the computer.Using the XOR and interleaving the mantissa of chaotic signals,a new chaotic signal is obtained,which has identical statistical characteristics to the uniformly distributed random sig-nal.The chaotic noised method provides a universal method to weaken the inherent structure of chaos and greatly expand the number of available chaotic systems that can be used for noise radar.2.The multivalued chaotic mapping property is studied,and a piecewise linear Lissajous chaotic system is proposed.Programming and encrypting radar waveform features with random noise in real-time can design a more flexible and secure radar system.Therefore,it is important to realize unpredictable signals based on chaotic systems.The analytical solution of Logistic map is analyzed,the form is general-ized,and the properties of the parameters and solutions are studied.If the numerical precision is unlimited,there are bounded,aperiodic and arbitrary step unpredictable sequences.This phenomenon is called the deterministic randomness,and the piecewise linear Lissajous chaotic:map is an important implementation(model)to generate an unpredictable sequence.3.The design of ultra-low sidelobe radar waveform is studied,and an iterative numerical optimization method to minimize the peak sidelobe level is proposed.The radar waveform design and selection mechanism based on prior information of the environment and target scene are important for adaptive radar,and the iterative nu-merical optimization method can perform a dynamic and multi-parameter constrained radar waveform design.Specifically,the dynamic peak-to-average power ratio can be designed to suppress the radar waveform of the sidelobes in the specified delay interval.Simultaneously,the two main steps of the algorithm are optimized on computing speed for engineering applications.Combining the initial sensitivity,noise-like characteris-tic and good correlation performance of chaos,the iterative numerical optimization method can generate MIMO radar waveform sets with large samples.4.The compressed sensing chaotic radar imaging algorithm is studied;a chaotic-based measurement matrix design method and a compressed sensing reconstruction algorithm are proposed.According to the radar imaging model,the echo signal is a linear combination of the emitted waveform delayed versions,and the combination coefficients are exactly backscattering coefficients of the target field.A statistically in-dependent chaotic radar waveform is designed,and the matrix composed of its delayed form is pruned to construct a measurement matrix.The simulation results show that the chaotic measurement matrix has equivalent performance to most random measure-ment matrices,but it is easier to implement.In the aspect of a compressed sensing reconstruction algorithm,exploiting the global optimization feature of the bat algo-rithm and ergodicity of chaos,a chaotic bat algorithm-generalized orthogonal matching pursuit(CBA-GOMP)reconstruction method is proposed.The CBA-GOMP algo-rithm has almost identical performance to the GOMP algorithm,but it has obvious processing speed advantage for large-scale problems.