基于循环谱相关的雷达信号脉内分析改进算法

针对传统的雷达信号脉内特征分析算法存在的局限,提出了一种基于循环谱相关的雷达信号脉内特征分析的改进算法。该算法将传统的循环谱估计方法进行了改进,能对雷达信号脉内调制方式进行识别并提取脉内特征参数,然后结合改进的小波变换的优点,对识别出的相位编码信号进行相位突变点的提取,最后输出至完善的脉冲描述字中。改进的算法能够在较低计算量的同时保证较好的脉内特征参数的估算精度。仿真结果表明,在较低信噪比下,该算法仍然具有较好的性能。     

Moving horizon based wavelet de-noising method of dual-observed geomagnetic signal for nonlinear high spin projectile roll positioning

Phase-frequency characteristics of approximate sinusoidal geomagnetic signals can be used for projectile roll positioning and other high-precision trajectory correction applications. The sinusoidal geomagnetic signal deforms in the exposed and magnetically contaminated environment. In order to preciously recognize the roll information and effectively separate the noise component from the original geomagnetic sequence, based on the error source analysis, we propose a moving horizon based wavelet de-noising method for the dual-observed geomagnetic signal filtering where the captured rough roll frequency value provides reasonable wavelet decomposition and reconstruction level selection basis for sampled sequence; a moving horizon window guarantees real-time performance and non-cumulative calculation amount. The complete geomagnetic data in full ballistic range and three intercepted paragraphs are used for performance assessment. The positioning performance of the moving horizon wavelet de-noising method is compared with the band-pass filter. The results show that both noise reduction techniques improve the positioning accuracy while the wavelet de-noising method is always better than the band-pass filter. These results suggest that the proposed moving horizon based wavelet de-noising method of the dual-observed geomagnetic signal is more applicable for various launch conditions with better positioning performance.     

软件无线电数字信号处理器体系结构研究

软件无线电因被认为是无线通信技术未来的发展趋势而受到广泛关注.目前数字信号处理器是软件无线电发展的瓶颈.通过分析、比较目前几种较为典型的软件无线电数字信号处理器结构,归纳总结各种结构各自设计出发点和优缺点,并对软件无线电数字信号处理器的发展趋势做了展望.     

An INS/GNSS integrated navigation in GNSS denied environment using recurrent neural network

In view of the failure of GNSS signals, this paper proposes an INS/GNSS integrated navigation method based on the recurrent neural network (RNN). This proposed method utilizes the calculation principle of INS and the memory function of the RNN to estimate the errors of the INS, thereby obtaining a continuous, reliable and high-precision navigation solution. The performance of the proposed method is firstly demonstrated using an INS/GNSS simulation environment. Subsequently, an experimental test on boat is also conducted to validate the performance of the method. The results show a promising application prospect for RNN in the field of positioning for INS/GNSS integrated navigation in the absence of GNSS signal, as it outperforms extreme learning machine (ELM) and EKF by approximately 30% and 60%, respectively.     

基于GUI和矢量信号源的微波着陆信号模拟器设计

提出了基于GUI和矢量信号源的微波着陆信号模拟器设计方法。首先利用MATLAB图形用户界面开发环境设计了集信号参数设置、干扰模拟和基带数据生成于一体的基带波形仿真功能;其次提出了一种改进的扫描波束模拟方法,实现了对微波着陆扫描信号的精确模拟;最后利用矢量信号源MG3700A对基带数据进行混合调制。测试结果表明,该信号模拟器达到设计要求。     

飞行器有源对消隐身技术

隐身技术已经成为现代高性能飞行器设计的重要支撑,是先进战机的基本要求。现行的隐身设计方法主要包括气动外形优化以及隐身材料涂覆。随着雷达探测能力的不断提升,尤其在米波雷达探测背景下,外形优化与隐身涂层变得不再有效,有源隐身技术被重新予以重视并有望成为新的隐身技术突破点。本文着重分析了有源对消技术的基本概念、技术现状以及相应的关键技术,对该技术体制的优势和特点进行了归纳和总结。     

基于数字信道化的极微弱信号载波频率引导模块设计与实现

针对深空探测中常规点数的FFT无法对极微弱信号进行精确的频率引导,而超长点数的FFT无法用现有器件实现,提出一种基于数字信道化的并行FFT频率引导方法.接收信号先经过数字信道化处理,均匀划分为若干窄带信号,然后分别对各子带信号进行FFT运算,最后通过对各子带有效谱线的联合检测完成载波频率的精确估计.在等效219点FFT的频率引导模块FPGA实现中,通过FFT模块的复用节约了硬件资源开销.测试结果表明:在8MHz采样率下该模块的测频精度小于10Hz.     

A novel noise reduction technique for underwater acoustic signals based on complete ensemble empirical mode decomposition with adaptive noise,minimum mean square variance criterion and least mean square adaptive filter

Underwater acoustic signal processing is one of the research hotspots in underwater acoustics. Noise reduction of underwater acoustic signals is the key to underwater acoustic signal processing. Owing to the complexity of marine environment and the particularity of underwater acoustic channel, noise reduction of underwater acoustic signals has always been a difficult challenge in the field of underwater acoustic signal processing. In order to solve the dilemma, we proposed a novel noise reduction technique for underwater acoustic signals based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), minimum mean square variance criterion (MMSVC) and least mean square adaptive filter (LMSAF). This noise reduction technique, named CEEMDAN-MMSVC-LMSAF, has three main advantages: (i) as an improved algorithm of empirical mode decomposition (EMD) and ensemble EMD (EEMD), CEEMDAN can better suppress mode mixing, and can avoid selecting the number of decomposition in variational mode decomposition (VMD); (ii) MMSVC can identify noisy intrinsic mode function (IMF), and can avoid selecting thresholds of different permutation entropies; (iii) for noise reduction of noisy IMFs, LMSAF overcomes the selection of decomposition number and basis function for wavelet noise reduction. Firstly, CEEMDAN decomposes the original signal into IMFs, which can be divided into noisy IMFs and real IMFs. Then, MMSVC and LMSAF are used to detect identify noisy IMFs and remove noise components from noisy IMFs. Finally, both denoised noisy IMFs and real IMFs are reconstructed and the final denoised signal is obtained. Compared with other noise reduction techniques, the validity of CEEMDAN-MMSVC-LMSAF can be proved by the analysis of simulation signals and real underwater acoustic signals, which has the better noise reduction effect and has practical application value. CEEMDAN-MMSVC-LMSAF also provides a reliable basis for the detection, feature extraction, classification and recognition of underwater acoustic signals.     

基于粒子群算法的宽带真延时平面阵列方向图综合

针对大阵元间距平面阵列方向图综合问题,提出基于粒子群算法的宽带真延时平面阵列方向图综合方法。该方法根据真延时条件下阵列方向图主瓣和栅瓣指向的特点,采用宽带真延时抑制阵列方向图的栅瓣；利用粒子群优化算法优化阵列结构,得到具有较高主副瓣比的平面阵列方向图。通过对8×8的矩形平面阵进行仿真,验证了所提方法的有效性,在此基础上,还仿真研究了该方法对栅瓣的抑制性能与信号带宽之间的关系。     

基于功率谱的舰船水压信号检测方法研究

为了有效地从风浪背景下检测舰船水压场信号,鉴于舰船水压场信号与海浪水压信号在频谱上的差异,采用求卓越频率下的功率谱的方法对信号进行检测,取窗宽20s,每次计算21个采样点,分别求取海浪水压场的仿真信号及不同波浪级别下海上某目标的水压场实测数据的功率谱进行信号检测,验证了方法的有效性。