一种针对恒模信号的运动单站直接定位算法

相比于常规的"测向+位置估计"两步定位模式,以Weiss等提出的目标直接位置确定(DPD)算法具有估计精度高、分辨能力强和无需数据关联等诸多优点。基于该类定位算法的基本理念,提出了一种利用单个运动天线阵列对恒模(即相位调制)信号的DPD算法。首先,依据最大似然(ML)准则以及恒模信号的恒包络特征,建立了相应的直接定位优化模型;接着,根据优化函数的代数特征提出了一种有效的多参量交替迭代算法,用以获得ML估计器的最优数值解;此外,推导了针对恒模信源的位置直接估计方差的克拉美罗界(CRB),从而为新算法的定位精度提供定量的理论下界。仿真实验表明:相比于已有的基于单个运动天线阵列的直接定位算法以及传统的两步定位算法,通过利用恒模信号的恒包络特征可以明显提高目标直接定位的估计精度。     

Coherent Doppler tomography-a technique for narrow band SAR

Some concerns regarding a technique of narrowband synthetic aperture radar (N-SAR) imaging called coherent Doppler tomography (CDT), which may be a good candidate for spaceborne applications, are addressed. Using a single-frequency signal, are addressed. Using a single-frequency signal, resolution of two tenths of a wavelength can be achieved in the point spread function if the radar platform circles the ground path to be imaged. However, the high sidelobe level of -8-dB in the point spread function results in an unacceptable dynamic range. To reduce the sidelobe level, two approaches are presented: coherent processing using multiple discrete frequencies and noncoherent subaperture processing. Simulation results demonstrate that the sidelobe level is substantially reduced by both methods. However, the resolution is degraded and the computational overhead is greatly increased for noncoherent subaperture processing. Also presented is a possible satellite geometry configuration that could utilize N-SAR processing to provide high-resolution global mapping capability     

未知互耦条件下混合信号波达方向估计

阵列天线互耦对导向矢量的扰动以及信号相干性对数据协方差矩阵造成的秩损,使得基于子空间正交性原理的超分辨波达方向估计(Direction-of-Arrival,DOA)算法性能恶化,甚至失效。针对这一问题,提出一种在相干与非相干信号混合状态下无需阵列互耦补偿的特征矢量平滑DOA估计算法。该算法对部分阵元接收数据的协方差矩阵特征分解,将得到的特征矢量平滑处理后构造等效协方差矩阵,抑制阵列互耦影响的同时完成混合信号DOA估计。在阵列互耦和信号相干性均未知的条件下,正确估计了信号DOA,无需互耦参数估计或补偿。计算机仿真结果验证了算法的有效性。     

一种DS/FH混合扩频信号的并行捕获方法

为了解决低信噪比条件下高跳速DS/FH（直接扩频/跳频扩频）混合扩频信号的快速捕获问题,提出了一种FFT-IFFT（快速傅里叶变换-快速傅里叶逆变换）与非相干累加相结合的并行捕获算法。通过多支路同时运算的方式构建非相干累加矩阵,使非相干累加运算可以并行实施。分析表明,采用并行非相干累加后,既提高了捕获判决的准确性,又保证了捕获搜索的快速性。     

阵列宽带Lamb波在结构损伤检测中的应用

阵列信号处理中的空间谱估计可以对信号源进行辨别和定位,于是通过采集在结构上布置的阵列传感器Lamb波信号用来检测损伤发生的位置。通常,大多数空间谱估计方法均以窄带信号为假定,在很多基于Lamb波的结构损伤检测中,为了减小频散特性的影响,大多数研究以Lamb波为窄带信号进行分析,但无限窄的激励信号是物理不可实现的。因此,其在多数情况下Lamb波信号并不符合窄带信号假定,更应被认为是一种宽带信号来进行处理。进而利用空间谱估计中宽带信号非相干子空间处理方法（Incoherent Signal Subspace Method,ISM）中阵列接收的宽带Lamb波信号进行处理,检测出结构发生单一损伤时的损伤位置。随后,当结构损伤与边界反射波有叠加时会引起损伤信号相干,采用宽带信号相干子空间方法（Coherent Signal Subspace Method,CSM）对损伤位置进行检测,得到了较好的结果。     

Direction-of-arrival estimation using signal subspace modeling

A computationally viable algorithm for estimating the direction-of-arrival (DOA) of multiple wavefields that are incident on an array of sensors is developed. The geometry of the array is unrestricted and the incident wavefields may be generated by mixtures of incoherent and coherent emitting sources. In the approach taken, the sensor signals are modeled as a noise-contaminated linear combination of steering vectors which are functionally dependent on a set of DOA parameters. These parameters are to be chosen so that this sensor signal model is most compatible with empirically measured data (i.e., snapshot data). An iterative procedure is developed for selecting the most data compatible set of DOA parameters in both the snapshot domain and the array covariance matrix domain. Critical to the success of such iterative solution procedures is the generation of quality DOA parameters to initialize the algorithm. A sequential beamforming method for this initialization is presented. Numerical examples to illustrate the effectiveness of the proposed algorithmic approach are given     

确定相干机器多噪声源位置的方法研究

提出利用均匀线阵接收的数据构造一种矩阵进行奇异值（SVD）分解,以实现对相干噪声源的方位估计。利用这种方法,通过改变阵列中心位置便可确定机器多噪声源位置。计算机模拟和声学实验证实了这种方法的可行性。     

Acoustic node calibration using a moving source

Acoustic nodes, each containing an array of microphones, can track targets in x-y space from their received acoustic signals, if the node positions and orientations are known exactly. However, it is not always possible to deploy the nodes precisely, so a calibration phase is needed to estimate the position and the orientation of each node before doing any tracking or localization. An acoustic node can be calibrated from sources of opportunity such as beacons or a moving source. We derive and compare several calibration methods for the case where the node can hear a moving source whose position can be reported back to the node. Since calibration from a moving source is, in effect, the dual of a tracking problem; methods derived for acoustic target trackers are used to obtain robust and high resolution acoustic calibration processes. For example, two direction-of-arrival-based calibration methods can be formulated based on combining angle estimates, geometry, and the motion dynamics of the moving source. In addition, a maximum likelihood (ML) solution is presented using a narrowband acoustic observation model, along with a Newton-based search algorithm that speeds up the calculation the likelihood surface. The Cramer-Rao lower bound (CRLB) on the node position estimates is also derived to show that the effect of position errors for the moving source on the estimated node position is much less severe than the variance in angle estimates from the microphone array. The performance of the calibration algorithms is demonstrated on synthetic and field data.     

A direct position determination method with combined TDOA and FDOA based on particle filter

The localization of a stationary transmitter using moving receivers is considered. The original Direct Position Determination (DPD) methods, with combined Time Difference of Arrival (TDOA) and Frequency Difference of Arrival (FDOA), do not perform well under low Signal-to-Noise Ratio (SNR), and worse still, the computation cost is difficult to accept when the computational capabilities are limited. To get better positioning performance, we present a new DPD algorithm that proves to be more computationally efficient and more precise for weak signals than the conventional approach. The algorithm partitions the signal received with the same receiver into multiple non-overlapping short-time signal segments, and then uses the TDOA, the FDOA and the coherency among the short-time signals to locate the target. The fast maximum likelihood estimation, one iterative method based on particle filter, is designed to solve the problem of high computation load. A secondary but important result is a derivation of closed-form expressions of the Cramer-Rao Lower Bound (CRLB). The simulation results show that the algorithm proposed in this paper outperforms the traditional DPD algorithms with more accurate results and higher computational efficiency, and especially at low SNR, it is more close to the CRLB.     

一种基于三维阵列结构二维波达方向估计的新方法

给出了一种在高斯白噪声环境下对多个窄带信号进行二维波达方向估计的新方法.该方法根据给出的天线阵列结构的特点,首先构造四个相关矩阵,进而构造一个大的矩阵,对其进行一次特征值分解,由ESPRIT原理实现了信号波达方向的准确估计.该方法精度较高,不存在错误估计,有一定的实用性.     

General direction-of-arrival estimation: a signal subspace approach

A high-resolution algorithm is presented for resolving multiple incoherent and coherent plane waves that are incident on an array of sensors. The incident sources can be a mixture of narrowband and broadband sources, and, the geometry of the array is unrestricted. The algorithm makes use of a fundamental property possessed by those eigenvectors of the array spectral density matrix that are associated with eigenvalues that are larger than the sensor noise level. Specifically, it is shown that these eigenvectors can each be represented as linear combinations of the steering vectors identifying the incident plane waves. This property is then used to solve the important special cases of incoherent sources incident on a general array and coherent sources incident on an equispaced linear array. Simulation results are presented to illustrate the high-resolution performance achieved with this approach relative to that obtained with MUSIC and spatial smoothed MUSIC in which the coherent-signal-subspace focusing method is used     

Frequency-Agile Radar Signal Processing

Modern radars may incorporate pulse-to-pulse carrier frequency modulation to increase probability of detection, to reduce Vulnerability to jamming, and to reduce probability of interception. However, if coherent processing is used for clutter rejection, the frequency of N consecutive pulses must be held constant for N-pulse clutter cancellation or Doppler filtering. If M pulses are transmitted during the time the antenna illuminates a target, there are M/N coherently integrated echoes available for noncoherent integration in the computer or the operator's display to further improve the signal-to-noise ratio (SNR). In this paper, analytical and simulation methods are employed to determine the balance between coherent and noncoherent integration that yields the greatest SNR improvement. Attention is focused upon a model using peak selection of fast Fourier transform (FFT) Doppler channels and is compared to a reference model involving only a single Doppler channel. Curves of detectable SNR as a function of M and N are presented for both models.     

Digital channelized receiver based on time-frequency analysis for signal interception

A digital channelized receiver is presented for the interception of a wide variety of signals of complex structure, including those with low probability of interception. The receiver is designed from the perspective of the time-frequency analysis. It uses an extended time-frequency representation based on the noncoherent integration of the short-time Fourier transform (STFT) on which the detection system and the encoder work. The encoder includes robust frequency estimation, automatic modulation recognition, and clustering, to handle broadband and simultaneous signals and to prevent out-of-channel detections (a typical phenomenon in channelized receivers). The receiver has been evaluated for a wide range of signals and shows a good performance in terms of detection, estimation, and processing of simultaneous signals. Signals collected from real-life systems and synthetic signals have been utilized.     

嵌套阵列最大似然估计测向算法

针对在辐射源个数未知的条件下嵌套阵列难以估计多个辐射源角度的问题,提出了基于最大似然估计(MLE)的嵌套阵列角度估计算法。算法在嵌套阵列模型的基础上,首先通过推导阵列截获多辐射源信号的最大似然函数及其梯度,利用最速下降法估计出空域中所有潜在辐射源的角度;然后,通过多元假设检验,利用最大似然比与门限进行比较,确定出空域中所有潜在辐射源中某一时刻发射信号的活跃辐射源角度,排除其余噪声形成的虚假辐射源角度,解决了在辐射源个数未知条件下嵌套阵列对多个辐射源角度估计问题。仿真结果表明:与传统多重信号分类(MUSIC)算法相比,该算法在辐射源数目未知、存在相干信号、低信噪比(SNR)、低快拍数条件下,均具有较好的角度估计精度,并且算法形成的虚拟阵列自由度是空间平滑MUSIC算法的2倍;多元假设检验法比传统信源数目估计算法在低信噪比条件下和处理相干信号方面具有明显优势。     

修正容积卡尔曼滤波数据域直接定位算法

为解决数据域直接定位（DPD）算法面临的计算压力,提高算法效率,提出一种基于修正的容积卡尔曼滤波（MCKF）的DPD算法。首先,融合各观测信号波达方向信息,利用子空间数据融合方法建立一种基于间接观测量的DPD滤波模型;然后,根据模型特点设计MCKF算法进行求解,解决间接观测量带来的噪声累积问题;最后,对算法计算量进行分析和对比,说明计算效率的提升。仿真结果表明,所提算法与基于最大似然遍历搜索和遗传算法的DPD算法相比,在相同的估计性能下,计算量下降明显,时效性显著提升,增加了算法实用价值。     

Direction-finding with sparse rectangular dual-size spatialinvariance array

A novel sparse array geometry embedding two sizes of spatial invariances is presented for use with a new ESPRIT-based (estimation of signal parameters via rotational invariance techniques) algorithm for aperture extension. The half-wavelength invariance yields unambiguous but high-variance direction cosine estimates to disambiguate low-variance but cyclically ambiguous estimates from the larger invariance. With larger invariance at 60 half-wavelengths, resolution threshold for two closely spaced emitters is reduced by 50 dB and estimation error by 100-fold. Array design formulas are also presented     

Basic Concepts in the Processing of SARSAT Signals

Search and rescue satellite-aided tracking (SARSAT) involves the use of satellites in low-polar orbits which relay the emergency signals of distressed vehicles to an earth station for signal analysis. In this paper, we present some basic concepts and a theoretical analysis of the spectra produced by coherent and noncoherent emergency locator transmitter signals. It is shown that coherent signals can be easily processed using linear spectral analysis. Noncoherent signals, however, require more advanced methods.     

聚焦变换在MIMO阵列方位估计中的应用

MIMO阵列是近年来信号处理领域提出的一种新体制阵列技术,可有效避免常规阵列中的相干源问题。为解决多载波造成的方位模糊,提出了一种基于聚焦变换的MIMO阵列目标方位估计方法。该方法将MIMO阵列接收信号分解为多个频率分量的信号,并通过聚焦算法将多个频率信号聚焦到同一信号子空间,然后对聚焦后的信号进行方位估计。仿真结果表明:与直接对MIMO阵列接收信号进行方位估计相比,该方法利用了MIMO阵列的回波不相干性和宽带信号能量,具有更好的分辨能力和更高的方位估计精度。     

A Comparison of Noncoherent and Coherent MTI Improvement Factors

An analysis based on statistical considerations and Monte Carlo simulations indicates that a noncoherent moving target indicator (MTI) using a linear envelope detector differs from one using a square law envelope detector. The square law envelope detector is usually described in the literature because of ease of analysis, and it is commonly stated or implied that the results are the same for the two cases because of the similar spectral characteristics of the detectors. A comparison is made between the two noncoherent MTIs and the coherent MTI in terms of clutter attenuation and MTI improvement factors.     

Angle of arrival estimation of coherent signals using an arraydoublet in motion

Shown here is how the estimation of signal parameters via relational invariance techniques (ESPRIT) algorithm may be used with a single pair of antennas in motion to estimate angles of arrival (AOA) for coherent signals. The approach exploits the Doppler frequency shifts caused by the doubler in motion. With this estimator, the number of signals that can be handled is not limited by the size of the array, as in the usual ESPRIT application, but by an adjustable parameter. A theoretical performance analysis of the estimator and typical examples showing the use of this estimator are given