A simple generation approach for chaotic sequences with Gauss probability distribution is proposed. Theoretical analysis and simulation based on Logistic chaotic model show that the approach is feasible and effective....A simple generation approach for chaotic sequences with Gauss probability distribution is proposed. Theoretical analysis and simulation based on Logistic chaotic model show that the approach is feasible and effective. The distribution characteristics of the novel chaotic sequence are comparable to that of the standard normal distribution. Its mean and variance can be changed to the desired values. The novel sequences have also good randomness. The applications for radar mask jamming are analyzed.展开更多
As the amount of data produced by ground penetrating radar （GPR） for roots is large, the transmission and the storage of data consumes great resources. To alleviate this problem, we propose here a root imaging algor...As the amount of data produced by ground penetrating radar （GPR） for roots is large, the transmission and the storage of data consumes great resources. To alleviate this problem, we propose here a root imaging algorithm using chaotic particle swarm optimal （CPSO） compressed sensing based on GPR data according to the sparsity of root space. Radar data are decomposed, observed, measured and represented in sparse manner, so roots image can be reconstructed with limited data. Firstly, radar signal measurement and sparse representation are implemented, and the solution space is established by wavelet basis and Gauss random matrix; secondly, the matching function is considered as the fitness function, and the best fitness value is found by a PSO algorithm; then, a chaotic search was used to obtain the global optimal operator; finally, the root image is reconstructed by the optimal operators. A-scan data, B-scan data, and complex data from American GSSI GPR is used, respectively, in the experimental test. For B-scan data, the computation time was reduced 60 % and PSNR was improved 5.539 dB; for actual root data imaging, the reconstruction PSNR was 26.300 dB, and total computation time was only 67.210 s. The CPSO-OMP algorithm overcomes the problem of local optimum trapping and comprehensively enhances the precision during reconstruction.展开更多
该文在步进频信号的基础上,把基于混沌调制的多载波相位编码(Multi-Carrier Phase Coded,MCPC)信号作为子脉冲,用Costas跳频代替频率的线性步进,设计出脉间Costas跳频脉内多载波混沌相位编码(Inter-Pulse Costas frequency hopping and ...该文在步进频信号的基础上,把基于混沌调制的多载波相位编码(Multi-Carrier Phase Coded,MCPC)信号作为子脉冲,用Costas跳频代替频率的线性步进,设计出脉间Costas跳频脉内多载波混沌相位编码(Inter-Pulse Costas frequency hopping and intra-pulse Multi-Carrier Chaotic Phase Coded,IPC-MCCPC)雷达信号,并对其模糊函数及自相关性能进行了研究。仿真分析表明,该文设计的信号继承了步进频信号用较小的瞬时带宽合成较大的工作带宽的优点,同时有效克服了步进频信号存在的距离-速度耦合的缺点。脉内多载波特性使得这种信号在保持总带宽和步进频信号相等的条件下减少跳频阶数,从而提高信号处理的数据率;混沌调相的引入使得这种信号具有更强的保密性;脉间频率的随机跳变使其模糊函数具有更低的周期性旁瓣。这种信号众多的参数、灵活的结构及较大的调制复杂度,增加了侦察接收机匹配和识别的难度,从而提高雷达的反截获性能。展开更多
针对传统混沌雷达对多目标测距困难的问题,提出了一种建立在解析解系统上的混沌雷达多目标测距方法。该方法使用解析解混沌系统中的连续信号作为雷达发射信号,并把解析解混沌系统中的二值离散序列经移位寄存器保存在雷达接收端,通过保...针对传统混沌雷达对多目标测距困难的问题,提出了一种建立在解析解系统上的混沌雷达多目标测距方法。该方法使用解析解混沌系统中的连续信号作为雷达发射信号,并把解析解混沌系统中的二值离散序列经移位寄存器保存在雷达接收端,通过保存的二值离散序列能够准确重构雷达发射信号模板。使用该模板和回波信号进行匹配滤波,通过匹配滤波输出信号的峰值得到待测目标的距离。该方法能够在-10 d B信噪比条件下实现多目标测距,且雷达接收端因为只需保存二值离散信号所以需要的存储空间小,实现过程成本低廉。仿真实验验证了提出方法的有效性。展开更多
Orthogonal waveform design is quite an important issue for waveform diversity systems. A chaos based method for the orthogonal discrete frequency coding waveform （DFCW） design is proposed to increase the insufficien...Orthogonal waveform design is quite an important issue for waveform diversity systems. A chaos based method for the orthogonal discrete frequency coding waveform （DFCW） design is proposed to increase the insufficient orthogonal waveform number and their finite coding length. Premises for chaos choosing and the frequency quantification method are discussed to obtain the best correlation properties. Simulation results show the validity of the theoretic analysis.展开更多
基金This work was supported by the NEW Laboratory Funding under Grant No.w090403.
文摘A simple generation approach for chaotic sequences with Gauss probability distribution is proposed. Theoretical analysis and simulation based on Logistic chaotic model show that the approach is feasible and effective. The distribution characteristics of the novel chaotic sequence are comparable to that of the standard normal distribution. Its mean and variance can be changed to the desired values. The novel sequences have also good randomness. The applications for radar mask jamming are analyzed.
基金supported by the Fundamental Research Funds for the Central Universities(DL13BB21)the Natural Science Foundation of Heilongjiang Province(C2015054)+1 种基金Heilongjiang Province Technology Foundation for Selected Osverseas ChineseNatural Science Foundation of Heilongjiang Province(F2015036)
文摘As the amount of data produced by ground penetrating radar （GPR） for roots is large, the transmission and the storage of data consumes great resources. To alleviate this problem, we propose here a root imaging algorithm using chaotic particle swarm optimal （CPSO） compressed sensing based on GPR data according to the sparsity of root space. Radar data are decomposed, observed, measured and represented in sparse manner, so roots image can be reconstructed with limited data. Firstly, radar signal measurement and sparse representation are implemented, and the solution space is established by wavelet basis and Gauss random matrix; secondly, the matching function is considered as the fitness function, and the best fitness value is found by a PSO algorithm; then, a chaotic search was used to obtain the global optimal operator; finally, the root image is reconstructed by the optimal operators. A-scan data, B-scan data, and complex data from American GSSI GPR is used, respectively, in the experimental test. For B-scan data, the computation time was reduced 60 % and PSNR was improved 5.539 dB; for actual root data imaging, the reconstruction PSNR was 26.300 dB, and total computation time was only 67.210 s. The CPSO-OMP algorithm overcomes the problem of local optimum trapping and comprehensively enhances the precision during reconstruction.
文摘针对传统混沌雷达对多目标测距困难的问题,提出了一种建立在解析解系统上的混沌雷达多目标测距方法。该方法使用解析解混沌系统中的连续信号作为雷达发射信号,并把解析解混沌系统中的二值离散序列经移位寄存器保存在雷达接收端,通过保存的二值离散序列能够准确重构雷达发射信号模板。使用该模板和回波信号进行匹配滤波,通过匹配滤波输出信号的峰值得到待测目标的距离。该方法能够在-10 d B信噪比条件下实现多目标测距,且雷达接收端因为只需保存二值离散信号所以需要的存储空间小,实现过程成本低廉。仿真实验验证了提出方法的有效性。
基金supported by the Hunan Province Distinguished Ph.D. Innovation Fund (CX2012B018)the National University of Defense Technology Distinguished Ph.D. Innovation Fund (B120403)
文摘Orthogonal waveform design is quite an important issue for waveform diversity systems. A chaos based method for the orthogonal discrete frequency coding waveform （DFCW） design is proposed to increase the insufficient orthogonal waveform number and their finite coding length. Premises for chaos choosing and the frequency quantification method are discussed to obtain the best correlation properties. Simulation results show the validity of the theoretic analysis.
