基于电侦相控阵的机载AESA信号认知

发布时间：2018-06-07 15:36

本文选题：宽带信号认知 + 宽带波达方向估计　；参考：《西安电子科技大学》2014年硕士论文

【摘要】：机载电子扫描阵列(AESA,Active Electronically Scanned Array)的发射信号具有大带宽、低信噪比、信号特征多变等特点,导致采用传统的电子侦察手段难以截获和认知这种信号。针对机载AESA信号的低截获对我国电子侦察能力带来的挑战,本文开展了基于电侦相控阵的机载AESA信号认知方法和方案设计的研究。针对机载AESA信号大带宽、低信噪比的特点,提出了基于电侦相控阵的非相干积累频谱支撑区提取的子带频域多目标超分辨测向方法。首先,对每个通道的数字基带采样信号沿快时间采用快速傅里叶变换转换到频域;其次,对每个通道的频域表示沿空域叠加,实现AESA信号频谱的非相干积累;然后,寻找非相干积累后频谱的所有峰值,排序后按一定比例取部分最小峰值的均值作为参考门限,高于参考门限给定阈值的频点作为AESA信号的频谱支撑区;接着,根据孔径渡越带宽的一定比例对频谱支撑区划分子带,将子带内的频点多通道数据作为频域快拍;随后,基于非相干处理模式对每个子带分别采用频域快拍和迭代自适应算法(IAA,Iterative Adaptive Approach)实现超分辨波达方向估计,通过累加获得整个频域支撑区的宽带空间谱估计;最后,使用相干信号子空间类算法对宽带信号进行了聚焦处理,提高了算法的估计性能和实时性能。基于56元等距线阵的仿真结果表明,只要宽带信号无频谱混叠,所提方法在信噪比低至-20dB时仍然具有良好的超分辨波达方向估计性能。针对复杂电磁环境导致AESA信号分选困难的问题,基于信号波达方向估计,采用宽带波束形成时域结构,实现AESA信号的空域增强和其他电侦信号的空域抑制。仿真结果表明,宽带波束形成时域结构能够有效分离多个宽带信号,从而实现信号分选。在宽带波束形成分选电侦信号的基础上,实现了机载AESA信号的多参数认知,这些参数包括信号的到达时间(TOA,Time of Arrival)、脉冲宽度(PW,Pulse Wide)、脉冲重复间隔(PRI,Pulse Repetition Interval)、信号频谱带宽及中心频率。以机载AESA信号认知的关键技术为支撑,设计了宽带信号认知处理系统的硬件实现方案。首先,在宽带信号认知需求的基础上,规划了以FPGA+多核DSP处理器为架构的信号处理系统整体框架,给出了系统中各模块的功能,并讨论了数据处理流程。然后,完成了系统总体状态机的设计,进而细化到自检、工作、校正三种工作状态。最后,以提出的非相干积累频谱支撑区提取的子带频域多目标超分辨测向方法为例,基于多核DSP处理器TMS320C6678设计了该方法的软件处理流程,并进行了多核任务划分和核间通信讨论。
[Abstract]:The transmitted signals of airborne electronic scanning array (Aesa) active Electronically Scanned Array) are characterized by large bandwidth, low signal-to-noise ratio (SNR) and variable signal characteristics, which makes it difficult to intercept and recognize such signals by traditional electronic reconnaissance techniques. Aiming at the challenge posed by the low interception of airborne AESA signal to the electronic reconnaissance capability of our country, the cognitive method and scheme design of airborne AESA signal based on the phased array of electrical detection are studied in this paper. Aiming at the characteristics of large bandwidth and low signal-to-noise ratio (SNR) of airborne AESA signals, a multi-target super-resolution direction finding method in sub-band frequency domain based on the non-coherent integration spectrum support region is proposed. First, the digital baseband sampling signal of each channel is converted to frequency domain by fast Fourier transform along the fast time; secondly, the frequency domain representation of each channel is superposed along the spatial domain to realize the incoherent accumulation of AESA signal spectrum. After searching for all the peaks of the spectrum after incoherent accumulation, the average value of the partial minimum peak value is taken as the reference threshold according to a certain proportion, and the frequency points above the given threshold value of the reference threshold are used as the spectral support region of the AESA signal. According to a certain proportion of the aperture transit bandwidth, the spectrum supports the molecular band, and the multi-channel data of frequency points in the sub-band are taken as frequency domain rapid-shot. Based on the incoherent processing mode, each subband is estimated by frequency domain rapid-beat and iterative adaptive Adaptive algorithm, which is used to estimate the direction of arrival (DOA) of super-resolution, and the wideband spatial spectrum estimation of the whole support region in frequency domain is obtained by summing up. The coherent signal subspace algorithm is used to focus the wideband signal, which improves the estimation performance and real-time performance of the algorithm. The simulation results based on 56 element equidistant linear array show that as long as there is no spectrum aliasing in wideband signal, the proposed method still has a good performance of super-resolution DOA estimation when the SNR is low to -20 dB. Aiming at the difficulty of AESA signal sorting caused by complex electromagnetic environment, based on DOA estimation, wideband beamforming time domain structure is adopted to realize spatial enhancement of AESA signal and spatial suppression of other electrical detection signals. Simulation results show that the wideband beamforming time domain structure can effectively separate multiple wideband signals and realize signal sorting. On the basis of wideband beamforming, the multi-parameter cognition of airborne AESA signal is realized. These parameters include the arrival time of signal, pulse width, pulse Repetition intervalation, signal spectrum bandwidth and center frequency. Based on the key technology of airborne AESA signal cognition, the hardware implementation scheme of broadband signal cognitive processing system is designed. Firstly, based on the cognitive requirements of wideband signals, the overall framework of signal processing system based on FPGA multi-core DSP processor is planned, the functions of each module in the system are given, and the data processing flow is discussed. Then, the design of the system state machine is completed, and then it is refined to three working states: self-checking, working and correcting. Finally, taking the proposed sub-band frequency domain super-resolution direction finding method based on the non-coherent integration spectrum support region as an example, the software processing flow of the method is designed based on the multi-core DSP processor TMS320C6678. Multi-nuclear task partitioning and inter-nuclear communication are discussed.
【学位授予单位】：西安电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN911.7

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