Performance of a Square Law Pseudonoise Ranging Time-of-Arrival Estimator

The performance of a square law time-of-arrival (TOA) estimator that has been proposed for use in ASTRO-DABS, part of a possible satellite-based fourth generation air traffic control system is considered. The transmitted message consists of a pulse amplitude modulated (PAM) ranging sequence that, due to transmitter characteristics, is corrupted by an unknown frequency offset. The optimum TOA estimator, for the case of no frequency uncertainty, is first presented, together with a lower bound on the variance of the estimate generated. This is followed by the consideration of a suboptimum TOA estimator for which a high signal-to-noise ratio (SNR) performance analysis is carried out; here, the effects of frequency uncertainty are included. Next, the zero-crossing properties of the derivative of the (suboptimum) estimation statistic are presented and the results used to derive an upper bound to the TOA estimate variance that is valid for all SNR values. This latter result is significant because it displays the system threshold effect and complements performance lower bounds that may be derived via other methods. In addition, the method presented here may be applied to other optimum and suboptimum systems where a discrete set of parameters is to be estimated.     

Time delay estimation at high signal-to-noise ratio

The estimation of the delay between two signals is examined in the limit of high signal-to-noise ratio (SNR). It is shown that for the case of white noise, cross correlation with no prefiltering approaches the optimal maximum-likelihood (ML) estimator as the SNR grows to infinity. In simulation experiments with SNRs greater than 1, it outperforms the approximate ML estimator, which is based on estimated spectra. Other algorithms, such as generalized cross correlation or parameter estimation algorithms, are shown to be suboptimal at high SNRs     

白天大气层内星敏感器观星能力分析

利用星敏感器进行白天大气层内观星,首先要解决的问题是强天空背景的干扰。通过对白天天空背景和不同光谱恒星的特点进行分析,提出了光谱滤波和偏振成像加形态学滤波和多帧图像累加的技术路线,综合利用光学方法和图像处理方法提高观测对比度和信噪比。给出了白天观星的信噪比模型,并在不同天空背景偏振度条件下,得出了G、K、M光谱恒星的0至5等星的单帧图像信噪比和对应的使CCD(Charge Coupled Device,电荷耦合器件)接近饱和的极限曝光时间。结果表明:星等值越低,天空背景偏振度越大,则信噪比越高;同等条件下,信噪比由小到大依次为G、K、M光谱恒星;而对于低信噪比的图像,通过多帧累加后可满足观测的要求。     

基于2－D熵的机载SAR图像分割迭代算法研究

机载合成孔径雷达(SAR)图像可用于检测识别机场跑道.由于SAR图像包含大量噪声,算法抗噪性能对于SAR图像处理很重要.2-D阈值方法的分割效果比传统的一维方法要好,特别是对受噪声影响的图像.然而,2-D阈值方法耗时长,难以实用.因此,本文在现有的2-D熵迭代分割算法的基础上提出了一种基于二维直方图统计特点的最大熵阈值分割算法.通过大量试验证明,本文提出的方法不仅获得了理想的分割效果,而且进一步提高了二维阈值选取速度.     

Angular Tracking of Two Closely Spaced Radar Targets

Bounds on the accuracy of unbiased estimates of the angular coordinates of a target, in the presence of a nearby interfering target, have previously been determined. These bounds allow for the angular resolution of two CW targets to an extent limited only by the signal-to-noise ratio (SNR). An SNR of 40 dB will allow two targets to be resolved at less than one-fifth beamwidth (?/2 X) separation, for most values of target relative phase angles. The maximum-likelihood estimator for this problem, based on the outputs of a plane circular array of receiving elements, is found and simplified. An analog realization of the two-target maximum-likeli-hood processor is presented. This realization has the simple form of two single-target trackers each tracking one of the targets, linked by a decoupling network which accounts for the interference produced in each by the presence of a second target, when the targets are separated by less than a beamwidth. Results of an analog-computer simulation of the system are given and discussed. Finally an application to the finite-size single-target problem is given.     

A Correlation Polarimeter for Noise-Like Signals

Optimum estimation (tracking) of the polarization plane of a linearly polarized electromagnetic wave is determined when the signal is a narrow-band Gaussian random process with a polarization plane angle which is also a Gaussian random process. This model is Compared to previous work and is applicable to space communication. The estimator performs a correlation operation similar to an amplitude -comparison monopulse angle tracker, giving the name correlation polarimeter. Under large signal-to-noise ratio (SNR), the estimator is causal. Performance of the causal correlation polarimeter is evaluated for arbitrary SNR. Optimum precorrelation filtering is determined. With low SNR, the performance of this system is far better than that of previously developed systems. Practical implementation is discussed. A scheme is given to reduce the effect of linearly polarized noise.     

基于自适应步长选择的周期格型线搜索估计

稀疏、含噪观测条件下周期点过程的周期估计是一个经典的信号处理问题。针对该问题,提出了一种格型线搜索(LLS)算法,该算法通过数值方式搜索似然函数的最大值,但其性能取决于人为预先选取的搜索步长。推导了一个步长计算公式,并利用该公式改进了LLS算法。改进的LLS算法能够自适应选择搜索步长,其达到的克拉美-罗界(CRLB)的信噪比(SNR)门限与最大似然估计(MLE)算法一致,但计算复杂度比后者低一个多的数量级。性能分析与仿真实验表明,所提算法比已有算法能更好地实现估计精度与复杂度的折中。     

一种频域插值变化迭代频率估计方法

针对现有频率估计算法存在的复杂度高、频率估计能力弱、估计结果均方差大等缺点,在固定迭代AM（Aboutanios—Mulgrew）无偏频率估计算法基础上,提出一种频域插值变化迭代频率估计算法,推导了不同迭代参数实现无偏估计的充分条件,证明了有偏估计时本算法的收敛性和偏离度,通过设置不同迭代参数,可以实现无偏或有偏估计。仿真分析表明：当具有较高信噪比时,在整个频率估计范围内,该方法均方误差接近CRLB（Cramer-RaoLowerBound,克拉美一罗下限）;当FFT（FastFourierTransform,快速傅里叶变换）粗估计残余频率接近0．5时,该方法的均方误差优于CRLB,为CRLB的96％。     

Bearings-only tracking of maneuvering targets using abatch-recursive estimator

We present a new batch-recursive estimator for tracking maneuvering targets from bearings-only measurements in clutter (i.e., for low signal-to-noise ratio (SNR) targets), Standard recursive estimators like the extended Kalman Iter (EKF) suffer from poor convergence and erratic behavior due to the lack of initial target range information, On the other hand, batch estimators cannot handle target maneuvers. In order to rectify these shortcomings, we combine the batch maximum likelihood-probabilistic data association (ML-PDA) estimator with the recursive interacting multiple model (IMM) estimator with probabilistic data association (PDA) to result in better track initialization as well as track maintenance results in the presence of clutter. It is also demonstrated how the batch-recursive estimator can be used for adaptive decisions for ownship maneuvers based on the target state estimation to enhance the target observability. The tracking algorithm is shown to be effective for targets with 8 dB SNR     

Computer Optimization of FM/FM Telemetry Systems

In this correspondence, the threshold carrier power of FM/FM systems and the receiver IF bandwidth are optimized through a computer program. For a typical set of IRIG (inter-range instrumentation group) channels, it is demonstrated that the required carrier signal-to-noise ratio can be as low as 5 dB (much less than the conventional 12 dB value) in order to maintain the subcarrier signal-to-noise ratio at 12 dB, the threshold level. comparison of the optimized and the conventional taper analysis is tabulated.     

利用α稳定分布的小波域SAR图像降斑算法

提出了一种改进的合成孔径雷达(SAR)图像α-MAP降斑算法,通过采用厚尾α稳定分布和引入噪声方差调整系数的方法,可以获得更好的降斑和纹理保持效果,同时应用平稳小波分解来解决Gibbs效应引入的伪噪声问题。最后通过对实际SAR图像的降斑处理,对本文的算法与最新的小波软阈值算法以及传统的局部自适应滤波器在性能参数和滤波效果上做了全面的比较。试验表明本文的算法更具适应性,实现了降斑与纹理保持更有效的综合滤波,在性能参数和复原图像效果上都有较好的表现。     

Optimum detection and location estimation of target lines in the range-time space of a search radar

The average likelihood ratio detector is derived as the optimum detector for detecting a target line with unknown normal parameters in the range-time data space of a search radar, which is corrupted by Gaussian noise. The receiver operation characteristics of this optimum detector is derived to evaluate its performance improvement in comparison with the Hough detector, which uses the return signal of several successive scans to achieve a non-coherent integration improvement and get a better performance than the conventional detector. This comparison, which is done through analytic derivations and also through simulation results, shows that the average likelihood ratio detector has a better performance for different SNR values. This result is justified by showing the disadvantages of the Hough method, which are eliminated by the optimum detector. To have an estimate for the location of the detected target line in the optimum detection method as the Hough method, which detects and localizes the target lines simultaneously, we present the maximum a posteriori probability estimator. The estimation performance of the two methods is then compared and it is shown that the maximum a posteriori probability estimator localizes the detected target lines with a better performance in comparison with the Hough method.     

Radar power multiplier for acquisition of low observables using anESA radar

In this paper the acquisition of a low observable (LO) incoming tactical ballistic missile using the measurements from a surface based electronically scanned array (ESA) radar is presented. We present a batch maximum likelihood (ML) estimator to acquire the missile while it is exo-atmospheric. The proposed estimator, which combines ML estimation with the probabilistic data association (PDA) approach resulting in the ML-PDA algorithm to handle false alarms, also uses target features. The use of features facilitates target acquisition under low signal-to-noise ratio (SNR) conditions. Typically, ESA radars operate at 13-20 dB, whereas the new estimator is shown to be effective even at 4 dB SNR (in a resolution cell, at the end of the signal processing chain) for a Swerling III fluctuating target, which represents a significant counter-stealth capability. That is, this algorithm acts as an effective “power multiplier” for the radar by about an order of magnitude. An approximate Cramer-Rao lower bound (CRLB), quantifying the attainable estimation accuracies and shown to be met by the proposed estimator, is derived as well     

Multiple radar targets estimation by exploiting induced amplitude modulation

This work deals with the problem of estimating complex amplitudes, Doppler frequencies, and directions of arrival (DOA) of multiple targets present in the same range-azimuth resolution cell of a surveillance radar. The maximum likelihood (ML) and the asymptotic (large sample size) ML (AML) estimators are derived. To reduce the computational complexity of the maximization of the nonlinear two-dimensional criterion function of the AML estimator, we propose a computationally efficient algorithm based on the RELAXation method. It allows decoupling the problem of jointly estimating the parameters of the signal components into a sequence of simpler problems, where the parameters of each component are separately and iteratively estimated. The proposed method overcomes the resolution limitation of the classical monopulse technique and resolves multiple targets exhibiting an arbitrarily small difference in azimuth as long as their Doppler frequencies differ at least by the inverse of the number of integrated pulses, provided that enough signal-to-noise ratio (SNR) per pulse is available. The performance of the proposed AML-RELAX estimator is numerically investigated through Monte Carlo simulation and Cramer-Rao lower bound (CRLB) calculation.     

The split symbol moments SNR estimator in narrow-band channels

The split symbol moments estimator (SSME) is an algorithm that is designed to estimate symbol signal-to-noise ratio (SNR) in the presence of additive white Gaussian noise (AWGN). The performance of the SSME algorithm in bandlimited channels is examined, and the effects of the resulting intersymbol interference (ISI) are quantified. All results obtained are in closed form and can be easily evaluated numerically for performance-prediction purposes. The results are also validated through digital simulations     

改进的自适应阈值软硬折中Curvelet图像去噪技术

Curvelet变换是继小波变换和Ridgelet变换之后,更适合图像处理的一种多尺度变换,它能同时获得对图像平滑区域和边缘部分的稀疏表达,且具有很强的方向性。针对软阀值和硬阈值去噪方法存在的不足,提出了基于Curvelet变换域的软硬阈值折中去噪法,并采用不同的阈值自适应地对不同的Curvelet子带进行阈值化,实验结果表明该方法对图像中的边缘曲线特征有更好的复原。去噪后图像PSNR值更高,视觉效果更好。     

Angular Accuracy of a Scanning Radar Employing a Two-Pole Filter

A two-pole filter is proposed as a detector for a scanning radar. The optimum values of the filter coefficients are found and are approximated by a simple expression. The optimum two-pole filter requires a 0.15-dB increase in signal-to-noise ratio in order to provide the same detection capability as the optimum detector, and yields azimuth estimates whose standard deviation are within 15 percent of the Cramér-Rao lower bound. The estimator is simple to implement, avoiding the storage requirements of the moving window detector and the bias complications of the feedback integrator.     

Low observable target motion analysis using amplitude information

In conventional passive and active sonar system, target amplitude information (AI) at the output of the signal processor is used only to declare detections and provide measurements. We show that the AI can be used in passive sonar system, with or without frequency measurements, in the estimation process itself to enhance the performance in the presence of clutter where the target-originated measurements cannot be identified with certainty, i.e., for “low observable” or “dim” (low signal-to-noise ratio (SNR)) targets. A probabilistic data association (PDA) based maximum likelihood (ML) estimator for target motion analysis (TMA) that uses amplitude information is derived. A track formation algorithm and the Cramer-Rao lower bound (CRLB) in the presence of false measurements, which is met by the estimator even under low SNR conditions, are also given. The CRLB is met by the proposed estimator even at 6 dB in a cell (which corresponds to 0 dB for 1 Hz bandwidth in the case of a 0.25 Hz frequency cell) whereas the estimator without AI works only down to 9 dB. Results demonstrate improved accuracy and superior global convergence when compared with the estimator without AI. The same methodology can be used for bistatic radar     

The Resolution Performance of Range Estimators

The theoretical basis and methods of implementation of a moment algorithm for the range separation estimation of two closely spaced point targets are presented. Moment estimation and noise filtering techniques introduced here result in a considerable improvement over Baum's algorithm. The error bounds are established and it is shown that the spectral moment estimator exhibits optimum (zero bias, minimum variance) performance when the target separation normalized to the standard deviation of the Gaussian pulse is 2?1.5. Monte Carlo simulation is performed to verify the approximations made and to demonstrate the feasibility of the working models.