DOA estimation method for wideband signals by sparse recovery in frequency domain

The traditional super-resolution direction finding methods based on sparse recovery need to divide the estimation space into several discrete angle grids, which will bring the final result some error. To this problem, a novel method for wideband signals by sparse recovery in the frequency domain is proposed. The optimization functions are found and solved by the received data at every frequency, on this basis, the sparse support set is obtained, then the direction of arrival (DOA) is acquired by integrating the information of all frequency bins, and the initial signal can also be recovered. This method avoids the error caused by sparse recovery methods based on grid division, and the degree of freedom is also expanded by array transformation, especially it has a preferable performance under the circumstances of a small number of snapshots and a low signal to noise ratio (SNR).

Detection of Number of Wideband Signals Based on Support Vector Machine

In array signal processing,number of signals is often a premise of estimating other parameters.For the sake of determining signal number in the condition of strong additive noise or a little sample data,an algorithm for detecting number of wideband signals is provided.First,technique of focusing is used for transforming signals into a same focusing subspace.Then the support vector machine(SVM)can be deduced by the information of eigenvalues and corresponding eigenvectors.At last,the signal number can be determined with the obtained decision function.Several simulations have been carried on verifying the proposed algorithm.

DOA estimation method for wideband signals by block sparse reconstruction

For the direction of arrival（DOA） estimation,traditional sparse reconstruction methods for wideband signals usually need many iteration times.For this problem,a new method for two-dimensional wideband signals based on block sparse reconstruction is proposed.First,a prolate spheroidal wave function（PSWF） is used to fit the wideband signals,then the block sparse reconstruction technology is employed for DOA estimation.The proposed method uses orthogonalization to choose the matching atoms,ensuring that the residual components correspond to the minimum absolute value.Meanwhile,the vectors obtained by iteration are back-disposed according to the corresponding atomic matching rules,so the extra atoms are abandoned in the course of iteration,and the residual components of current iteration are reduced.Thus the original sparse signals are reconstructed.The proposed method reduces iteration times comparing with the traditional reconstruction methods,and the estimation precision is better than the classical two-sided correlation transformation（TCT）algorithm when the snapshot is small or the signal-to-noise ratio（SNR） is low.

Wideband Signal Detection Based on MWC Discrete Compressed Sampling Structure

In order to solve the cross-channel signal problem caused by the uniform channelized wideband digital receiver when processing wideband signal and the problem that the sensitivity of the system greatly decreases when the bandwidth of wideband digital receiver increases,which both decrease the wideband radar signal detection performance,a new wideband digital receiver based on the modulated wideband converter(MWC)discrete compressed sampling structure and an energy detection method based on the new receiver are proposed.Firstly,the proposed receiver utilizes periodic pseudo-random sequences to mix wideband signals with baseband and other sub-bands.Then the mixed signals are low-pass filtered and downsampled to obtain the baseband compressed sampling data,which can increase the sensitivity of the system.Meanwhile,the cross-channel signal will all appear in any subbands,so the cross-channel signal problem can be solved easily by processing the baseband compressed sampling data.Secondly,we establish the signal detection model and formulate the criterion of the energy detection method.And we directly utilize the baseband compressed sampling data to carry out signal detection without signal reconstruction,which decreases the complexity of the algorithm and reduces the computational burden.Finally,simulation experiments demonstrate the effectiveness of the proposed receiver and show that the proposed signal detection method is effective in low signal-to-noise ratio(SNR)compared with the conventional energy detection and the probability of detection increases significantly when SNR increases.

Wideband signal detection based on high-speed photonic analog-to-digital converter

This Letter demonstrates the effectiveness of a high-speed high-resolution photonic analog-to-digital converter （PADC） for wideband signal detection. The PADC system is seeded by a high-speed actively mode locked laser, and the sampling rate is multiplied via a time-wavelength interleaving scheme. According to the laboratory test, an X-band linear frequency modulation signal is detected and digitized by the PADC system. The channel mismatch effect in wideband signal detection is compensated via an algorithm based on a short-time Fourier transform. Consequently, the signal-to-distortion ratio （SDR） of the wideband signal detection is enhanced to the comparable SDR of the single-tone signal detection.

New direction of arrival estimation method for wideband coherent signals

To estimate the direction-of-arrival （DOA） of wideband coherent signals, a new method by modifying the orthogonality of the projected suhspaces method is proposed. And it can deal with randomly position perturbed arrays by using the Toeplitz method. This method needn＇t the primary information of DOA for focusing matrix and the sector dividing of interpolated method, which improving the precision of estimation and reducing the computational complexity. Simulations illustrate the effectiveness of this method.

Wideband angle of arrival estimation of chirp signals using virtual Wignerville distribution

To estimate the angle of arrivals （AOA） of wideband chirp sources, a new timo-frequency algorithm is proposed. In this method, virtual sensors are constructed based on the fact that the steering vectors of wideband chirp signals are linear and vary with time. And the randon Wignersville distribution （RWVD） of real sensors and virtual sensors are calculated to yield the new time-invariable steering vectors, furthermore, the noise and cross terms are suppressed. In addition, the multiple chirp signals are selected by their time-frequency points. The cost of computation is lower than the common AOA estimation methods of wideband sources due to nonrequirement of frequency focusing, interpolating and matrix decomposition, including subspace decomposition. Under the lower signal noise ratio （SNR） condition, the proposed method exhibits better precision than the method of frequency focusing （FF）. The proposed method can be further applied to nonuniform linear array （NLA） since it is not confined to the array geometry. Simulation results illustrate the efficacy of the proposed method.

Application of Mellin Transform in Wideband Underwater Acoustic Signal Processing

According to the features of the wideband underwater acoustic signals,an algorithm for the wideband ambiguity function is put forward based on Mellin transform.The wideband acoustic signal processing using the fast Mellin transform is also explored.The theoretical analysis and simulation results show that the algorithm has not only high computation efficiency but also good concentration in wideband ambiguity domain.It suits for the wideband underwater acoustic signal processing.

Mathematical Formulations of Signal Propagation in Ultra-Wideband Transceiver Systems under a UWB Channel Environment with an Extension of Frequency Offset Correction

This paper analyzes mathematically the crucial aspects of signal processing in a Multi-Band (MB) Orthogonal Frequency Division Multiplexing (OFDM) based system considering Ultra-Wideband (UWB) channel environment. In the process of analysis, it emphasizes the significant features of UWB receiver design in comparison with ‘conventional’ narrow-band system. The analysis shows that the high dispersive nature of a frequency selective UWB channel effects the design of different signal processing blocks like pre-select filter, low noise amplifier (LNA) and analog-to-digital (A/D) converter in the receiver front end. The characteristic functions of each of these stages are now dominated by the channel characteristics and it needs to be modified accordingly. This analysis is extended further with the study of frequency offset error and its correction. The unbiased Cramer Rao Lower Bound (CRLB) of estimation error is calculated and supported by computer simulation. The performance of an MB-OFDM system with frequency offset correction in terms of Bit-Error-Rate (BER) is also reported.

基于GPU的北斗B1宽带复合信号实时发生器设计

为了实现北斗B1C+B1I信号的联合生成,提出一种基于软件无线电和图形处理器(graphics processing unit,GPU)加速的北斗B1宽带复合信号的实时生成方法,该方法针对单边带复数二进制偏移载波(single-sideband complex binary offset carrier,SCBOC)调制方式的信号体制进行设计,系统根据用户配置的接收机运动轨迹和星历文件,生成中频信号并通过射频端发射。为了进一步提升GPU并行运算速度,从优化设备内存结构、设计并行线程架构和统一计算设备架构流(compute unified device architecture stream,CUDA)加速3个方面,设计了基于异步运算的加速采样点数据计算的CUDA优化实现方案。测试结果证明,优化后的算法可以基于SCBOC调制实时生成北斗B1I+B1C信号,基于GTX3060的GPU平台,信号90 M采样率下能实现8颗卫星复合信号的实时生成。

基于Radon变换的宽带信号多域参数同时测量方法

实际电子监测设备的作战环境复杂多变,辐射源个数、工作频率、工作带宽、到达角度等多域参数信息对于实现工作场景的实时精确感知至关重要。提出一种基于Radon变换的宽带信号多域参数同时测量方法,实现多个宽带信号多域重点工作参数的同时快速测量,大大提升低信噪比条件下监测目标特性的多维实时感知能力。该方法结合数字信道化结构及二重FFT算法实现全侦收频段及全侦收角度的空时域联合功率聚焦,并生成作战场景的空时二维频谱幅度图,利用Radon变换算法实现不同映射角度的线性积分运算,构建合适的检测门限,推导计算全场景多目标多参数测量结果。实验显示,该方法可以有效提升弱信号的参数测量精度,实现多目标多域参数同时测量。

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.

频域宽带阵列波束形成技术优化设计

为提高宽带相控阵系统的波束合成性能,文章针对宽带相控阵系统中的延时补偿问题,采用频域宽带阵列波束形成的方法,分析了宽带相控阵中应用交叠FFT进行时延补偿的原理和误差造成的原因;基于一个接收信号带宽为600 MHz的64阵元的宽带相控阵系统,研究了子阵规模、FFT点数、交叠率、位宽、采样率等交叠FFT参数对延时精度、信号保真度和波束性能的影响,在满足工程应用要求的同时对频域宽带阵列波束合成技术进行了优化;经研究确定子阵规模不超过9个天线阵元、FFT点数不小于512、交叠率不小于1/16、位宽不小于采用12 bit时可以达到指标的要求,为交叠FFT方法应用在实际工程中提供了依据与参考,并使其工程实现复杂度降低。

Dual-assisted high-precision tracking technique for wideband multiplexed signals in new generation GNSS

With the evolution of Global Navigation Satellite System(GNSS),new generation GNSS signals have adopted the dual-frequency multiplexing modulation techniques,which jointly modulate multiple signals located on multiple sub-frequencies into a Wideband Multiplexed Signal(WMS).Although WMSs were proposed initially to reduce the complexity of satellite transmitters and improve the transmission efficiency of signals,their multi-component structures and wide root mean square bandwidths introduced by high-frequency subcarriers also provide the possibility to improve the GNSS ranging precision.Therefore,this paper proposes a Dual-assisted Multi-component Tracking(DMT)technique,which can not only fully use high-frequency subcarriers in WMSs,but also effectively track carrier,subcarrier,and code by jointly utilizing all components in WMS.In this paper,the tracking and ranging performances of DMT are comprehensively analyzed theoretically and by simulation and real experiments.The results show that compared with existing WMS tracking methods,DMT can achieve tracking results with lower tracking jitters and ranging results with higher precision,providing a highly advantageous solution for new generation GNSS signal processing.

微波宽带超高精度双向时间比对技术研究

当前微波双向时间比对技术广泛应用于视距区域站间时间同步领域,能够达到纳秒站间时间同步水平,对于时间同步指标更高的应用场景还有待进一步提升。本文利用大带宽扩频信号和载波相位在时间测量性能方面的潜在优异性能,提出了基于宽带信号调制解调技术的微波双向载波相位时间比对方法,设计了原型试验系统,利用氢原子钟和相位微跃计验证了实验室条件下系统的测量不确定度(A类)0.27 ps和分辨力4 ps,达到了预期效果,为后续远距离试验和应用推广奠定了坚实的技术和试验基础。

基于二分搜索的宽带多普勒模型信号捕获方法

针对深空通信等超高动态低信噪比通信场景中,传统信号捕获方法存在着动态范围不足、精确度不够以及使用窄带多普勒模型导致对接收信号近似精确度不高的问题,提出一种基于二分搜索的接收端采样率调整方法。使用宽带多普勒模型对接收信号进行建模,并使用扫频余弦类信号进行多普勒频偏估计和定时估计,处理多普勒伸缩后的信号与本地信号采样率不匹配的问题。对所提方法进行同步性能仿真,仿真结果表明,所提方法采用正反扫频线性调频(UD-LFM)信号,能在信噪比为-49dB、最大多普勒频偏为2MHz的条件下,多普勒频偏估计误差小于400 Hz,定时估计误差不超过60 ns。相比不使用本文所提方法进行直接捕获,本文所提方法具有更高的捕获精确度以及更低的信噪比门限。

基于宽带相干信号子空间方法的超声导波长骨评价

超声导波对长骨的生物力学特性敏感,已经广泛应用于长骨的健康评价。由于骨骼的高衰减特性,准确估计长骨中宽带相干导波信号的频散模式,进而准确反演长骨材料特征参数,是骨超声领域的一个研究热点和难点。本文提出了一种基于宽带相干信号子空间的导波波数估计方法,高精度提取导波频散模式;在此基础上,应用具有全局优化特性的蚁群算法从导波模式中估计长骨材料参数,成功实现了对长骨状况的定量评价。仿真和离体实验(2块仿真样本和2块离体牛骨)共同验证了方法的有效性,实验频散与参考频散之间的相对误差分别为3.52%,3.83%,3.35%,4.51%;对于离体牛骨,皮质骨厚度、纵波速度、横波速度估计值与参考值之间的平均相对误差分别为3.10%,0.11%,0.03%。综上,本文提出的方法为定量超声长骨评价提供了新的借鉴,也可应用于其他固体波导频散的高精度提取和结构健康表征。

基于FPGA的多相频域脉冲压缩实现方法

随着高速ADC器件的发展及雷达系统性能需求,宽带线性调频信号在雷达系统中取得广泛应用。高速采样使得频域脉冲压缩点数增大,增加了处理延时与工程实现难度。FPGA接收ADC采样的宽带信号为时域抽取的多相分量的形式,采用多相的方法实现基于时域抽取与频域抽取的二维FFT与IFFT,能够节省FPGA存储资源,降低脉冲压缩的处理延时。

一种5~20 GHz超宽带移相器

基于SMIC 40 nm CMOS工艺设计了一款工作频率覆盖5~20 GHz的超宽带6位移相器。该移相器采用矢量合成结构,核心电路包括输入巴伦、正交信号发生器、矢量合成器和数模转换电路。正交信号发生器采用三级多相滤波结构,拓展了带宽。采用低误差和电流阵列控制结构的矢量合成器,实现了高的移相精度。后仿真结果表明,该移相器输入和输出回波损耗分别小于8.85 dB和10.12 dB,RMS相位误差小于1.52°,RMS增益误差小于0.17 dB。在2.5 V电源电压下功耗为43.50 mW。芯片面积为1.06 mm×0.80 mm。

分布式接收宽带多目标信号盲检测迭代处理方法

随着软硬件技术的飞速发展和宽带接收机的广泛使用,频谱检测向着高瞬时带宽的方向发展,传统基于信道化处理的频谱检测方法存在搜索速度慢、处理效率低下的问题。文章提出了1种新的分布式接收宽带多目标信号盲检测迭代处理方法,在无须预先知道信号数目及信号频谱位置的情况下,能够实现特定虚警概率多信号盲检测,具备较高的灵活性和稳健性。首先,在对信号特征进行分析的基础上,通过构造线性模型,将分布式接收多目标信号检测转化为线性模型求解问题进行处理;然后,基于贝叶斯多参数联合求解模型,在对未知参数先验分布进行合理假设的基础上,推导了各未知参数变分分布及信号检测门限的解析表达式,采用变分分布软信息迭代的方式实现多传感器信号、多参数联合估计,并利用每次迭代参数估计结果,对信号检测门限进行更新,通过置零操作实现预设虚警概率下的多信号盲检测;最后,通过仿真实验对所提方法性能进行了分析,并与相关方法进行了对比。仿真结果表明,所提方法能够有效利用多路接收信号信息,实现宽带未知多目标信号的盲检测,有效提升短数据下的算法处理效能,与现有方法相比,在接收单元数目较多以及信噪比较低时具有明显优势。