基于非均匀采样的光纤光栅解调系统

鉴于重叠多光纤Bragg光栅(FBG)传感器均匀采样时遇到的数据频谱混叠问题, 提出利用扫描周期随 机变化的正弦波实现传感FBG的非均匀采样方法,并在一种基于可调谐F-P滤波器的 FBG解调系统中得到成功应用。实验结果显示,本文方法能够很好避免混叠现 象,并且还能以低于Nyquist采样频率对信号进行采样分析。     

基于零电平处信号导数分析的分布式光纤传感定位算法研究

为了提高基于双Mach-Zehnder干涉(DMZI)原理的 分布式光纤传感系统的性能,提出一种 基于零电平处信号导数分析的快 速定位算法。利用信号在零电平处的导数大小,提取信号中最高频率附近的一段进行 时延估计,进而获得扰动发生位置。 由于提取信号的频率和带宽相对较大,因此系统的定位误差较小。与离散小波提取起始点信 号相比,本文算法能够适应更多的扰 动事件类型,且由于离散信号导数计算的复杂度远低于离散小波的傅里叶变换,运算时间大 幅降低,提高了系统的实时性。实 验结果表明,本文算法在10M/s采样率下,最大定位误差为 20m,而且计算时间少于0.13s。     

一种改进的低复杂度OFDM峰均比抑制PTS算法

针对正交频分复用系统中的信号峰值平均功率比问题,提出了一种基于时域采样点幅度筛选的低复杂度部分传输序列算法。算法通过设置信号经过逆向傅里叶变换后时域采样点的幅度之和为判别函数,并设置适当的幅度门限,筛选出幅度大于门限的信号采样点集合,利用该集合来搜索信号峰均比抑制相位因子,从而降低算法复杂度。仿真表明,与传统峰均比抑制算法相比,改进算法在保持峰均比抑制性能的同时降低了算法复杂度。     

基于FPGA的激光多普勒测长仪信号处理算法研究

针对激光多普勒测长仪多普勒频率的准确提取问 题,提出了一种基于FPGA的自适应采样频率的多普勒信号 处理算法。首先通过跟踪多普勒频率实现了采样频率的自适应选择,提高了低速测量的准确 度,扩大了系统的测速 范围;结合了FFT-FS频谱细化算法和比值校正算法,有效减小了测量误差,进一步提高了 多普勒频率提取的准确度; 最终通过多组长度测量实验,验证了算法的可行性,测量结果的相对误差优于0.1%。     

降低MIMO-OFDM系统峰均比的改进PTS算法

多输入多输出频分复用技术是将OFDM与MIMO技术相结合的无线通信系统,也具有OFDM系统存在的峰均比较高的问题。分析了MIMO-OFDM系统模型及PAPR问题,在次优PTS算法的基础上,提出了迭代限幅PTS联合算法。该算法先将MIMO-OFDM信号经过迭代PTS算法进行处理,然后再将其经过限幅处理进一步降低系统的PAPR。最后在自适应PTS算法的基础上进行了改进,仿真结果表明系统复杂度和PAPR性能有所降低,但可以通过调整门限来提高性能。     

5G NR小区搜索中一种频域相关快速同步算法

5G系统中随着带宽的不断增大,信号所承载的数据也在不断增加,LTE中定时同步方法应用在5G中增加了计算量。为了解决这个问题,提出了叠加与频域快速相关联合检测算法。该算法利用PSS信号(Primary Synchronization Signal, PSS)M序列特性,将本地3组PSS时域信号相加运算,然后进行频域转换,通过频域快速相关运算得到峰值位置,可以检测出粗同步点,再经过运算得到精同步点和小区组内ID号。数据分析表明,叠加与快速频域相关算法与经典算法相比在低信噪比环境下检测概率提升了约10%,算法复杂度降低了94.86%。     

Frequency estimation of sinusiode from wideband using sub-Nyquist sampling

A novel frequency estimation algorithm for wideband signal with sub-Nyquist sampling is proposed in this paper. With the aid of information provided by the auxiliary delayed sampling channel and the aliased frequency estimation for wideband signal with sub-Nyquist sampling, the frequency aliasing due to sub-Nyquist sampling can be solved. This method can reduce the complexity of the overall hardware at the cost of an auxiliary sampling channel. Furthermore, in order to alleviate the computation burden for its practicability, a more simplified algorithm is put forward and its validity is proved by our numerical simulation results. The Cramer-Rao Lower Bound （CRLB） of the frequency estimation is also derived at the end of this paper.     

A frequency offset estimation algorithm for OFDM systems

A new fine carrier frequency offset estimation algorithm in Orthogonal Frequency Division Multiplexing （OFDM） system is proposed. The correlation item is the training sequence instead of the received signal in the new algorithm. Simulation results show that the performance of the new algorithm is 4dB-9dB better than that of Schmidl＇s algorithm. Coarse frequency offset estimation is also discussed in this paper, which is the improvement of Zhang＇s method. The estimation range using the improvement method is twice as that using the Zhang＇s method. Based on the hardware of the receiver and the improved algorithm, a method using Fast Fourier Transform （FFT） is proposed to implement the coarse frequency estimation. The chip area of OFDM system can be reduced by using the proposed method.     

近红外可见光傅里叶变换光谱仪的参考激光数字倍频方法研究

近红外可见光傅里叶变换光谱仪需要使用倍频后的参考激光千涉信号作为采样信号。由于锁相环倍频无法适用于低频的非周期信号,而传统的数字倍频方法误差又较大,因此提出了一种经过改进的基于传统数字倍频方法的算法,并对其进行了仿真和验证。实验结果表明,算法改进后,输出波形的非均匀性误差从-2%~+1.6%提高到了-0.82%~+0.4%,说明由倍频产生的非均匀性误差得到了良好改善。     

An improved LMS algorithm for mode demultiplexing in frequency domain

In order to solve the problem that the traditional frequency domain least mean square(FD-LMS) algorithm will lose efficacy with the increase of differential mode group delay(DMGD) when the algorithm is used for demultiplexing of the 6×6 mode division multiplexing(MDM) system, an improved FD-LMS demultiplexing algorithm is proposed. By improving the error signal calculation method, the convergence performance of the output signal of the equalization filter is improved, and the steady-state error of the algorithm is reduced. Besides, the equalization performance of the traditional FD-LMS algorithm is compared with the improved FD-LMS algorithm. Simulation results show that the improved FD-LMS algorithm has great advantage over the traditional FD-LMS algorithm in demultiplexing performance on the premise that the computation complexity does not significantly increase. The optical signal to noise ratio(OSNR) penalty of the improved FD-LMS algorithm is 2.6 dB lower than that of traditional FD-LMS algorithm at a transmission distance of 80 km with DMGD is 50 ps/km.     

基于GA-MP的低复杂度OTFS检测算法

针对正交时频空(Orthogonal Time Frequency Space, OTFS)通信系统信号检测复杂度高的问题,提出一种改进的高斯近似消息传递(Gaussian Approximate Message Passing, GA-MP)检测算法。依据最大后验概率检测准则,对发送信号及隐变量进行逐符号高斯近似,基于置信传播算法与联合因子图进行消息传递,用边缘后验概率替代GA-MP中的外部信息以减少运算量,结合阻尼因子提升收敛速度,同时引入概率阈值减少后续更新的节点数,从而使运算复杂度得到有效降低。实验结果表明,改进后的GA-MP算法在保证误码率性能的前提下具有更低的复杂度。     

改进的“当前”统计模型变采样率目标跟踪算法

为满足实际雷达系统对高精度和高实时性的要求,提出了一种改进的"当前"统计模型变采样率机动目标跟踪算法。该算法针对"当前"统计模型必须预设加速度极值和机动频率的问题,提出一种加速度方差和机动频率在线同步自适应方法,建立改进的"当前"统计模型机动目标跟踪算法;针对在线自适应方法计算量大的问题,结合采样周期的大小与目标机动特性的关系,引入变采样率方法。仿真结果表明,与传统"当前"统计模型相比,改进的"当前"统计模型机动目标跟踪算法能显著提高对不同机动强度目标的跟踪精度;变采样率方法通过减少采样点数,节省了系统资源,提高了跟踪实时性;所提算法将两者结合,用传统的"当前"统计模型1.5~2倍的平均采样周期得到了更小的位置均方根误差,实现了用单模型方法同时改善跟踪精度和实时性的目的。     

Parameter estimation of weak space-based ADS-B signals using genetic algorithm

Space-based automatic dependent surveillance-broadcast (ADS-B) is an important emerging augmentation of existing ground-based ADS-B systems. In this paper, the problem of space-based ultra-long-range reception processing of ADS-B signals is described. We first introduce a header detection method for accurately determining the pulse position of a weak ADS-B signal. We designed a signal encoding method, shaping method, and fitness function. We then employed a genetic algorithm to perform high-precision frequency and phase estimations of the detected weak signal. The advantage of this algorithm is that it can simultaneously estimate the frequency and phase, meaning a direct coherent demodulation can be implemented. To address the computational complexity of the genetic algorithm, we improved the ratio algorithm for frequency estimation and raised the accuracy beyond that of the original ratio algorithm with only a slight increase in the computational complexity using relatively few sampling points.     

Feedforward symbol timing recovery technique using two samples per symbol

In this paper, a new feedforward symbol timing recovery technique using timing estimation followed by interpolation is presented for digital receivers with two samples/symbol or higher sampling rate. A few timing estimation algorithms are proposed to estimate the timing offset accurately. The basic algorithm uses only the in-phase (I) or quadrature (Q) signal for timing detection, which applies to a BPSK communication system. It is shown that the basic algorithm, when applied in quadrature modulation systems where both I and Q signals are available, can be modified slightly to yield an improved estimation precision. The mean and variance of the resulting timing estimate are analyzed and simulated, supporting a satisfactory estimation performance. It is also shown that by applying a postprocessing scheme, such as the Kalman filter, the variance can be further reduced, resulting in a smoothed timing estimate. Some of the issues concerning the implementation of the proposed technique are also addressed.     

星载AIS信号的频偏估计

星载自动识别系统(AIS)中信号存在严重的多普勒频偏,影响信号的正确解调,而传统的基于快速傅里叶变换(FFT)的频偏估计算法其估计范围无法满足需要.为此,提出了一种改进的自相关-FFT频偏估计算法,通过构造辅助函数以确定信号频偏的正负号,在此基础上对基于FFT的频偏估计算法进行改进,从而扩大频偏估计范围,实现对大的多普勒频移的估计.仿真和实验结果均表明,改进算法的频偏估计范围扩大为原来的2倍,具有很高的估计精度,十分接近修正后的克拉美罗界,且算法简单、易于实现.     

DCO-OFDM水下可见光通信系统的峰均比抑制算法

为了解决直流偏置光正交频分复用(DCO-OFDM)水下可见光通信系统中存在的高峰均功率比(PAPR)问题,采用了一种基于范德蒙类矩阵(VLM)预编码与改进的自适应缩放联合PAPR抑制的算法。首先,该算法利用VLM对频域信号进行预编码处理,以此降低其自相关性,再通过比值计算方式改进的自适应缩放因子对时域信号进行缩放,使其更好地减小发光二极管带来的非线性失真,最后实现了抑制系统PAPR的效果。结果表明,在互补累计分布函数为10-3时,相比于原始系统,此联合算法的PAPR下降了3.2dB。由此可知,该研究对抑制DCO-OFDM水下可见光通信系统的PAPR是有帮助的。     

Singular value analysis of the Jacobian matrix in microwave image reconstruction

For non-linear inverse scattering problems utilizing Gauss-Newton methods, the Jacobian matrix encodes rich information concerning the system performance and algorithm efficiency. In this paper, we perform an analytical evaluation of a single-iteration Jacobian matrix based on a previously derived nodal adjoint representation. Concepts for studying linear ill-posed problems, such as the degree-of-ill-posedness, are used to assess the impact of important system parameters on the expected image quality. Analytical singular value decomposition (SVD) of the Jacobian matrix for a circular imaging domain is derived along with the numerical SVD for optimizing imaging system configurations. The results show significant reductions in the degree-of-ill-posedness when signal frequency, antenna array density and property parameter sampling are increased. Specifically, the decay rate in the singular spectrum of the Jacobian decreases monotonically with signal frequency being approximately 1/3 of its 0.1 GHz value at 3 GHz, is improved with antenna array density up to about 35 equally-spaced circumferentially positioned elements and drops significantly with increased property parameter sampling to more than twice the amount of measurement data. These results should serve as useful guidelines in the development of design specifications for an optimized hardware installation.     

Low complexity joint estimation of synchronization impairments in sparse channel for MIMO–OFDM system

Low complexity joint estimation of synchronization impairments and channel in a single-user MIMO–OFDM system is presented in this paper. Based on a system model that takes into account the effects of synchronization impairments such as carrier frequency offset, sampling frequency offset, and symbol timing error, and channel, a Maximum Likelihood (ML) algorithm for the joint estimation is proposed. To reduce the complexity of ML grid search, the number of received signal samples used for estimation need to be reduced. The conventional channel estimation techniques using Least-Squares (LS) or Maximum a posteriori (MAP) methods fail for the reduced sample under-determined system, which results in poor performance of the joint estimator. The proposed ML algorithm uses Compressed Sensing (CS) based channel estimation method in a sparse fading scenario, where the received samples used for estimation are less than that required for an LS or MAP based estimation. The performance of the estimation method is studied through numerical simulations, and it is observed that CS based joint estimator performs better than LS and MAP based joint estimator.     

基于24 GHz FMCW 雷达的二维近场成像系统

为进行隐藏危险金属制品的安检,文中提出了一种24 GHz 低成本毫米波成像系统。该系统采用低成 本24 GHz 商用调频连续波(FMCW)雷达作为扫描源,在方位角和仰角上合成大孔径,使用二维十字扫描平台,经 FMCW 雷达信号处理以及合成孔径雷达(SAR)处理使隐藏物体成像。低成本的射频外设只提供了一路中频实信号 供ADC 采样量化,在图像重建中,文中提出将单路ADC 采样量化后的中频数字信号通过希尔伯特变换成复信号,对 复信号加布莱克曼窗优化频谱,再对信号序列补零以减小频域栅栏效应,后采用空间匹配滤波器补偿相位偏差,通 过FMCW 雷达近场成像原理对目标成像。改进后的算法适用于低成本的雷达前端系统,只需一路ADC 采集的中频 数字信号即可使成像系统达到理论的合成孔径成像分辨率。     

采用压缩感知的直扩测控信号处理

鉴于扩频测控系统宽带化带来的高速采样压力和高数据率问题,研究了基于压缩感知的直扩测控信号处理方法。通过深入分析直扩测控信号稀疏性,构造了延时-多普勒基字典,提出了基于压缩感知直扩测控信号处理框架,并针对直扩测控信号特点给出了改进正交匹配追踪重构算法,最后针对该信号处理方法的可行性和性能分别进行了仿真实验。仿真结果不仅验证了方法的可行性,同时表明可以在不影响解调性能条件下大幅度降低采样率或数据率,并具有一定的降噪效果,这将为直扩测控通信系统提供一种高效的模数转换和同步解调处理方式。