Simple and Efficient Nonparametric Method for Estimating the Number of Signals Without Eigendecomposition

Inspired by the computational simplicity and numerical stability of QR decomposition, a nonparametric method for estimating the number of signals without eigendecomposition (MENSE) is proposed for the coherent narrowband signals impinging on a uniform linear array (ULA). By exploiting the array geometry and its shift invariance property to decorrelate the coherency of signals through subarray averaging, the number of signals is revealed in the rank of the QR upper-trapezoidal factor of the autoproduct of a combined Hankel matrix formed from the cross correlations between some sensor data. Since the infection of additive noise is defused, signal detection capability is improved. A new detection criterion is then formulated in terms of the row elements of the QR upper-triangular factor when finite array data are available, and the number of signals is determined as a value of the running index for which this ratio criterion is maximized, where the QR decomposition with column pivoting is also used to improve detection performance. The statistical analysis clarifies that the MENSE detection criterion is asymptotically consistent. Furthermore, the proposed MENSE algorithm is robust against the array uncertainties including sensor gain and phase errors and mutual coupling and against the deviations from the spatial homogeneity of noise model. The effectiveness of the MENSE is verified through numerical examples, and the simulation results show that the MENSE is superior in detecting closely spaced signals with a small number of snapshots and/or at relatively low signal-to-noise ratio (SNR)     

A dense overlapped linear subarray architecture for interference suppressing in small‐scale arrays

Compared to omnidirectional antennas, smart antenna arrays are qualified such advantages as lower interference and better spatial reuse. As developed from large‐scale phased array radar, subarray technology is a key approach to reduce the computational complexity, and a quantity of algorithms for subarray partition and low sidelobe has been studied and applied in radar system. With the development of hardware manufacture, portability and mobility are the trend of devices, which limit the array aperture and number of elements, and the performances are constrained by elements number. This paper proposes a dense overlapped subarray architecture for linear array when elements number is small, to improve the array gain and output signal to interference plus noise ratio, and different weighting mode is employed at element and subarray level for adaptive digital beamforming to obtain special performances. The subarray partition is presented for the linear array, which keeps the spacing at subarray level half wavelength to avoid grating lobes and nulls, and the simulation results demonstrate that the subarray architecture induces better output signal to interference plus noise ratio; meanwhile, the computational amount is reduced. Copyright © 2014 John Wiley & Sons, Ltd.     

一种非均匀邻接子阵结构及其部分自适应处理性能分析

子阵级自适应处理可用较小的代价获得准最优的处理性能，对于幅度锥削的均匀线阵，本文提出用等噪声功率法来划分非均匀邻接子阵，计算机模拟结果表明该子阵结构的自适应方向图保形良好且没有明显栅瓣，其干扰抑制性能接近最优处理。     

平面数字阵列雷达的子阵级波束形成算法

大规模平面数字阵列雷达因为其优点得到广泛应用,但其全自适应处理实现困难,实际中广泛采用部分自适应处理,子阵结构就是其中的一种重要方法。该文针对有幅度加权的均匀平面阵,以各子阵噪声输出功率相等为原则进行非均匀邻接子阵划分,并通过归一化算法保证各子阵噪声功率相等,进而对平面阵子阵结构的波束形成性能进行了研究。计算机模拟仿真结果表明,该子阵结构的二维相扫和一维相扫的自适应方向图保形良好,可以达到与全自适应相接近的干扰抑制性能。     

一种低旁瓣子阵级自适应波束形成方法

相控阵雷达在军事上的应用日渐广泛,要满足雷达系统性能日益增长的需求,必须采用大孔径天线,以便得到更高的角度和距离分辨率。大型面阵的全自适应波束形成计算量庞大,采用子阵级自适应波束形成可以用较小的代价实现较优的自适应性能。研究了等幅平面阵的子阵级波束形成技术,并针对非均匀划分的子阵结构,采用了子阵级通道噪声功率的归一化处理。该方法不仅能够有效降低子阵级方向图的旁瓣电平,其自适应性能保持良好。仿真验证了该方法的有效性。     

The design of point detector arrays, I

This paper considers the design of a detection system to optimally detect known signal fields--scalar functions of a vector argument--corrupted by an additive noise field. The detection system has as its inputsnsamples (in Space) of the signal-plus-noise field; each spatial sample is the output of a point detector. Optimal processing of the point-detector outputs, as well as the locations of the point detectors, is considered. For a fixed array and under assumptions that are often physically reasonable, the optimum detector is separable into a spatial combiner and a temporal processor. The probability of error of the optimum detector is a monotonic function of the array gain. Convenient expressions of the array gain are found for circular arrays; by using these expressions, optimal radii for circular arrays are found.     

Object detection using high resolution near-field array processing

The authors present an algorithm for the detection and localization of an unknown number of objects buried in a halfspace and present in the near field of a linear receiver array. To overcome the nonplanar nature of the wavefield over the array, the full array is divided into a collection of subarrays such that the scattered fields from objects are locally planar at each subarray. Using the multiple signal classification (MUSIC) algorithm, directions of arrival (DOA) of locally planar waves at each subarray are found. By triangulating these DOAs, a set of crossings, condensed around expected object locations, are obtained. To process this spatial crossing pattern, the authors develop a statistical model for the distribution of these crossings and employ hypotheses testing techniques to identify a collection of small windows likely to contain targets. Finally, the results of the hypothesis tests are used to estimate the number and locations of the targets. Using simulated data, they demonstrate the usefulness and performance of this approach for typical background electrical properties and signal to noise ratios     

On the average near-far resistance for MMSE detection of directsequence CDMA signals with random spreading

The performance of a near-far-resistant, finite-complexity, minimum mean squared error (MMSE) linear detector for demodulating direct sequence (DS) code-division multiple access (CDMA) signals is studied, assuming that the users are assigned random signature sequences. We obtain tight upper and lower bounds on the expected near-far resistance of the MMSE detector, averaged over signature sequences and delays, as a function of the processing gain and the number of users. Since the MMSE detector is optimally near-far-resistant, these bounds apply to any multiuser detector that uses the same observation interval and sampling rate. The lower bound on near-far resistance implies that, even without power control, linear multiuser detection provides near-far-resistant performance for a number of users that grows linearly with the processing gain     

Joint space-time interpolation for distorted linear and bistatic array geometries

This paper presents a new joint space-time interpolation technique (STINT) to improve the small sample support performance of space-time adaptive processing (STAP) with distorted linear monostatic arrays and linear bistatic array configurations. Brennan's rule for the space-time clutter covariance matrix rank is extended to monostatic linear arrays with arbitrary intersensor spacing, distorted linear arrays and bistatic geometries. It is shown that both distortion in the array geometry and bistatic operation increase the clutter rank and cause the space-time clutter covariance matrix to become range dependent. This results in lower output signal-to-interference-plus-noise ratio (SINR) for the same number of adaptive degrees of freedom and reduced available sample support. This motivates the development of the STINT technique aimed at compensating for the clutter rank inflation, while also making the clutter statistics appear more stationary across range. More specifically, a linear transformation is designed that maps the received clutter across space and time to that which would be received by a "virtual" monostatic side-looking ULA. By mapping the data to form a reduced rank clutter covariance matrix, fewer snapshots are needed for a statistically stable matrix inversion as required in STAP, thereby improving the short observation time performance. Simulation results for a typical airborne radar scenario indicate up to 10-dB SINR improvement can be obtained using STINT with limited sample support.     

Landmine detection and localization using chemical sensor arrayprocessing

We develop methods for automatic detection and localization of landmines using chemical sensor arrays and statistical signal processing techniques. The transport of explosive vapors emanating from buried landmines is modeled as a diffusion process in a two-layered system consisting of ground and air. Measurement and statistical models are then obtained from the associated concentration distribution. We derive two detectors (the generalized likelihood ratio (GLR) test and the mean detector) and determine their performance in terms of the probabilities of false alarm and detection. To determine the unknown location of a landmine, we derive a maximum likelihood (ML) estimation algorithm and evaluate its performance by computing the Cramer-Rao bound (CRB). The results are applied to the design of chemical sensor arrays, satisfying criteria specified in terms of detection and estimation performance measures and for optimally selecting the number and positions of sensors and the number of time samples. To illustrate the potential of the proposed techniques in a realistic demining scenario, we derive a moving-sensor algorithm in which the stationary sensor array is replaced by a single moving sensor. Numerical examples are given to demonstrate the applicability of our results     

Computationally efficient subspace-based method for direction-of-arrival estimation without eigendecomposition

A computationally simple direction-of-arrival (DOA) estimation method with good statistical performance is attractive in many practical applications of array processing. In this paper, we propose a new computationally efficient subspace-based method without eigendecomposition (SUMWE) for the coherent narrowband signals impinging on a uniform linear array (ULA) by exploiting the array geometry and its shift invariance property. The coherency of incident signals is decorrelated through subarray averaging, and the space is obtained through a linear operation of a matrix formed from the cross-correlations between some sensor data, where the effect of additive noise is eliminated. Consequently, the DOAs can be estimated without performing eigendecomposition, and there is no need to evaluate all correlations of the array data. Furthermore, the SUMWE is also suitable for the case of partly coherent or incoherent signals, and it can be extended to the spatially correlated noise by choosing appropriate subarrays. The statistical analysis of the SUMWE is studied, and the asymptotic mean-squared-error (MSE) expression of the estimation error is derived. The performance of the SUMWE is demonstrated, and the theoretical analysis is substantiated through numerical examples. It is shown that the SUMWE is superior in resolving closely spaced coherent signals with a small number of snapshots and at low signal-to-noise ratio (SNR) and offers good estimation performance for both uncorrelated and correlated incident signals.     

Efficient quadratic detection in perturbed arrays via Fouriertransform techniques

Matched-field beamforming used in combination with a generalized likelihood ratio test is the most common detector structure in array processing situations. Unfortunately, various array perturbations caused by phase, calibration, propagation effects, or modeling errors can cause the sensor observations to become only partially correlated, limiting the performance of traditional matched-field beamformers that assume perfect coherence of the signal wavefronts. Quadratic array processing is optimal for many perturbed array problems; however, direct implementation poses a significant computational burden. We show that under certain conditions, the optimal quadratic detector for dealing with perturbed arrays can be approximately realized efficiently and robustly employing only discrete Fourier transforms to deal with spatial processing. In addition, we show that the proposed spatial processing allows for convenient integration of conventional frequency-domain methods for angle-of-arrival searches. Our proposed array detection structure provides the robustness and performance benefits of complicated quadratic processing at a computational cost comparable with that of traditional matched-field beamforming     

相控阵MIMO雷达抗干扰波束形成算法

面对复杂多变的干扰环境下目标检测问题,雷达系统需要更高的系统增益和自由度实现对副瓣电平的控制和有效的抗干扰处理。为此提出一种基于相控阵MIMO雷达的抗干扰波束形成算法,该算法有效利用相控阵MIMO兼具相控阵高增益与MIMO高系统自由度的特点,提高系统抗干扰性能。在阵列发射端进行子阵划分,子阵间发射正交波形,子阵内发射同一波形并形成固定零陷对抗干扰;在阵列接收端进行匹配滤波获得波形分集,通过加窗函数控制副瓣电平并重构数据协方差矩阵消除形成零陷对副瓣电平产生的影响。所提算法在复杂多变的干扰环境下能够保持低副瓣电平并形成密集零陷对抗空间干扰,同传统算法相比优势明显。仿真验证了算法的有效性。      

一种基于粒子群算法的多目标子阵划分优化方法

为了降低硬件成本和系统的复杂度,子阵划分对于大型的相控阵雷达来说是必要的。传统的子阵划分方法主要针对信号处理的单一性能指标优化。针对多项指标优化的问题,本文提出了一种基于粒子群算法的子阵划分结构优化算法,相对于传统的方法能够同时优化多项性能指标,提高信号处理的性能。通过对线性阵列的划分做仿真,展示了粒子群算法对子阵级波束形成多项性能指标的提高。      

Applications of cumulants to array processing. IV. Directionfinding in coherent signals case

For pt.III see ibid., vol.45, no.9, p.2253-64, 1997. We present a subspace-based direction finding method for coherent signal environments using an antenna array. Our method, which uses fourth-order statistics, is capable of resolving more signals than a comparable second-order statistics-based subspace method and is applicable to a larger class of arrays. The maximum number of signals resolvable with our method may exceed the number of sensors in the array. Only a uniform linear subarray is needed; the rest of the array may have arbitrary and unknown response and does not require calibration. On the other hand, the comparable second-order statistics-based method is limited to uniform linear arrays only. No search procedure is needed in our method. Simulation experiments supporting our conclusions are provided     

基于高斯方向图的二维子阵级相干源超分辨测向

二维子阵级超分辨测向在相控阵雷达中具有重要应用.本文研究适用于相干源的子阵级ML估计方法.提出了子阵级ML估计的信号模型.利用子阵相位中心与增益来构造简化的阵列流形,使相控阵的校正成本与代价得到较大的降低.引入加权网络对子阵输出进行后处理,大大提高了阵列处理的灵活性.构造了高斯模式的子阵方向图.与直接简化的阵列流形方法相比,基于高斯方向图的简化阵列流形方法克服了其测向范围无法调整的局限性,且能更好抑制旁瓣源.仿真结果证实了所提出方法的有效性.     

Multicell uplink spectral efficiency of coded DS-CDMA with randomsignatures

A simple multicell uplink communication model is suggested and analyzed for optimally coded randomly spread direct sequence code-division multiple access (DS-CDMA). The model adheres to Wyner's (1994) infinite linear cell-array model, according to which only adjacent-cell interference is present, and characterized by a single parameter 0⩽α⩽1. The discussion is confined to asymptotic analysis where both the number of users and the processing gain go to infinity, while their ratio goes to some finite constant. Single cell-site processing is assumed and four multiuser detection strategies are considered: the matched-filter detector, “optimum” detection with adjacent-cell interference treated as Gaussian noise, the linear minimum mean square error (MMSE) detector and a detector that performs MMSE-based successive interference cancellation for intracell users with linear MMSE processing of adjacent-cell interference. Spectral efficiency is evaluated under three power allocation policies: equal received powers (for all users), equal rates, and a maximal spectral efficiency policy. Comparative results demonstrate how performance is affected by the introduction of intercell interference, and what is the penalty associated with the randomly spread coded DS-CDMA strategy. Finally, the effect of intercell time-sharing protocols as suggested by Shamai and Wyner (1997) is also examined, and a significant system performance enhancement is observed     

Applications of detection and estimation theory to large array seismology

The statistical theory of signal detection and estimation has been applied to problems in large array seismology. Using this theory the structure of the optimum detector for a known signal and long observation time in additive Gaussian noise is derived. The array processing filter employed by the optimum detector is known as the maximum-likelihood filter. This filter also has the property that it provides a minimum-variance unbiased estimate for the input signal when it is not known, which is the same as the maximum-likelihood estimate of the signal if the noise is a multidimensional Gaussian process. A series of experiments was performed using data from the large aperture seismic array to determine the effectiveness of the maximum-likelihood method relative to simpler methods such as beam-forming. These results provide significant conclusions regarding the design and processing of data from large seismic arrays. The conventional and high-resolution estimation of the frequency-wavenumber spectrum of the background microseismic noise is also presented. The diffuse structure of this spectrum is shown to aid in explaining the relative performance of array processing methods.     

一种新的子阵结构及其自适应性能分析

在阵列信号处理中，大型阵由于系统结构复杂，成本较高，在实际应用中受到限制，而采用子阵结构则可以减少接收通道数，简化系统设计，降低成本。本文针对等幅均匀线阵提出了一种新的结构简单的子阵，并且通过打乱子阵排列的周期性以及保证各子阵输出噪声功率相等，该子阵的栅瓣效应几乎可以忽略且其自适应方向图保形良好。     

Radar wideband digital beamforming based on time delay and phase compensation

In conventional phased array radars, analogue time delay devices and phase shifters have been used for wideband beamforming. These methods suffer from insertion losses, gain mismatches and delay variations, and they occupy a large chip area. To solve these problems, a compact architecture of digital array antennas based on subarrays was considered. In this study, the receiving beam patterns of wideband linear frequency modulation (LFM) signals were constructed by applying analogue stretch processing via mixing with delayed reference signals at the subarray level. Subsequently, narrowband digital time delaying and phase compensation of the tone signals were implemented with reduced arithmetic complexity. Due to the differences in amplitudes, phases and time delays between channels, severe performance degradation of the beam patterns occurred without corrections. To achieve good beamforming performance, array calibration was performed in each channel to adjust the amplitude, frequency and phase of the tone signal. Using a field-programmable gate array, wideband LFM signals and finite impulse response filters with continuously adjustable time delays were implemented in a polyphase structure. Simulations and experiments verified the feasibility and effectiveness of the proposed digital beamformer.