Blind parameter estimation of pseudo-random binary code-linear frequency modulation signal based on Duffing oscillator at low SNR

Conventional parameter estimation methods for pseudo-random binary code-linear frequency modulation(PRBC-LFM)signals require prior knowledge,are computationally complex,and exhibit poor performance at low signal-to-noise ratios(SNRs).To overcome these problems,a blind parameter estimation method based on a Duffing oscillator array is proposed.A new relationship formula among the state of the Duffing oscillator,the pseudo-random sequence of the PRBC-LFM signal,and the frequency difference between the PRBC-LFM signal and the periodic driving force signal of the Duffing oscillator is derived,providing the theoretical basis for blind parameter estimation.Methods based on amplitude method,short-time Fourier transform method,and power spectrum entropy method are used to binarize the output of the Duffing oscillator array,and their performance is compared.The pseudo-random sequence is estimated using Duffing oscillator array synchronization,and the carrier frequency parameters are obtained by the relational expressions and characteristics of the difference frequency.Simulation results show that this blind estimation method overcomes limitations in prior knowledge and maintains good parameter estimation performance up to an SNR of-35 dB.

Long term integration of radar signals with unknown Doppler shift for ubiquitous radar

Ubiquitous radar is a new radar system that provides continuous and uninterrupted multifunction capability within a coverage volume. Continuous coverage from close-in ＂pop-up＂ targets in clutter to long-range targets impacts selection of waveform parameters. The coherent processing interval （CPI） must be long enough to achieve a certain signal-to-noise ratio （SNR） that ensures the efficiency of detection. The condition of detection in the case of low SNR is analyzed, and three different cases that would occur during integration are discussed and a method to determine the CPI is presented. The simulation results show that targets detection with SNR as low as -26 dB in the experimental system can possibly determine the CPI.

Novel Frame Shift and Integral Technique for Enhancing Low-Light-Level Moving Images

A novel frame shift and integral technique for the enhancement of low light level moving image sequence is introduced. According to the technique, motion parameters of target are measured by algorithm based on difference processing. To obtain spatial relativity, images are shifted according to the motion parameters. As a result, the processing of integral and average can be applied to images that have been shifted. The technique of frame shift and integral that includes the algorithm of motion parameter determination is discussed, experiments with low light level moving image sequences are also described. The experiment results show the effectiveness and the robustness of the parameter determination algorithm, and the improvement in the signal-to-noise ratio （SNR） of low light level moving images.

油气管道内检测新技术与装备的开发及应用

油气管道内检测是保障油气管道安全的最有效的技术措施之一,而近年来出现的高碳钢、大管径、高压力、高流速油气管道对内检测技术与装备提出了新的挑战。为此,在调研电磁内检测新技术、极低频微弱瞬态信号检测新技术以及油气管道内检测新装备工程应用的基础上,基于电磁信号的主动发射与接收实现金属缺陷的检测,研发出电磁控阵检测器新技术与装备;基于杜芬混沌振子对含噪信号进行检测,实现对噪声中的极低频信号的检测,研发出极低频瞬态微弱信号检测新方法与装备,并开展了实际检测工程验证。研究结果表明:(1)研发的电磁控阵内检测新技术,利用直流励磁磁场和高频激励磁场协同作用的机理,仅用小信号激励即可实现响应的摄动效果;(2)引入采集信息成分的压缩采样,可突破内检测器的速度瓶颈,使电磁控阵检测器的检测速度达到创世界记录的8 m/s;(3)研发的基于混沌的极低频微弱瞬态信号检测新方法,可突破高速运动条件下内检测器管外跟踪定位过程中接收信号微弱且持续时间短暂的技术瓶颈,将微弱瞬态信号实时检测的信噪比降低到-10 dB以下。结论认为,该新装备的优越性能已经在实际运行的油气管道检测工程中得到了检验,将为国内主干油气管道的安全运行提供技术支撑和设备保障。

DOA estimation based on multi-frequency joint sparse Bayesian learning for passive radar

This paper considers multi-frequency passive radar and develops a multi-frequency joint direction of arrival(DOA)estimation algorithm to improve estimation accuracy and resolution.The developed algorithm exploits the sparsity of targets in the spatial domain.Specifically,we first extract the required frequency channel data and acquire the snapshot data through a series of preprocessing such as clutter suppression,coherent integration,beamforming,and constant false alarm rate(CFAR)detection.Then,based on the framework of sparse Bayesian learning,the target’s DOA is estimated by jointly extracting the multi-frequency data via evidence maximization.Simulation results show that the developed algorithm has better estimation accuracy and resolution than other existing multi-frequency DOA estimation algorithms,especially under the scenarios of low signalto-noise ratio(SNR)and small snapshots.Furthermore,the effectiveness is verified by the field experimental data of a multi-frequency FM-based passive radar.

极低信噪比大多普勒频移条件下基于双谱实现载频提取

针对极低信噪比大多普勒频移条件下载波提取问题,提出了一种基于AR模型双谱估计的下变频时域抽取载波提取方案,并在此基础上提出了分通道的改进方案,以及对其进行了MATLAB仿真。仿真结果表明了该方案及改进方案的有效性。

深空通信中极低码率编码技术研究

针对深空通信极低信噪比环境下,通信距离大,信号衰减大等特点,阐述了深空通信对低码率码字的需求。介绍低码率码字的发展情况后,引入GLDPC码,分析了LDPC码和Hadamard码进行级联时存在的度为1的节点问题。将LDPC-Hadamard级联码进行优化,对优化后的LDPC-Hadamard码进行仿真。结果表明,极低信噪比下,低码率LDPC-Hadamard码性能较好,一定程度上能够满足深空通信等恶劣信噪环境下的需求。