基于相关与小波变换相结合的弱信号检测

针对强噪声背景中的弱信号检测问题,在传统的相关检测方法的基础上,利用小波良好的去噪性能,提出了相关检测与小波变换相结合的弱信号检测方法。仿真结果表明,该方法优于传统的相关检测方法,无须知道有用信号的先验知识和同步信号便可以有效的检测周期性弱信号,并获得更高的输出信噪比。     

北斗导航接收机频率稳定度传递算法

为了提高北斗导航接收机的灵敏度,提升其弱信号跟踪能力,通常需要利用长时间的相干积分来提高环路信噪比。但是,当相干积分时间加长到一定程度时,环路性能反而有所下降,信噪比提升也不能达到理论值。针对由剩余频率误差和晶振误差引起的相干积分能量损失问题,主要研究了频率偏差对环路跟踪性能的影响,并提出了利用频率稳定度传递策略辅助弱信号跟踪的方法,解决了北斗导航接收机弱信号跟踪性能提升的问题,最大程度地改善了相干积分的效果,实现了对弱信号的跟踪。利用软件接收机平台对提出的频率稳定度传递算法进行验证,仿真结果表明该算法可使环路信噪比提升4dB ~5dB,充分说明了其可行性及有效性。     

基于改进补零/差分的北斗弱信号捕获算法

北斗信号二次编码调制了速率为1kbps的NH码,频繁的比特跳变导致传统捕获算法的效果受到抑制,并且限制了积分时间的增长。为了实现北斗弱信号的捕获,提出了一种适合北斗弱信号的捕获算法,将补零算法和差分相干积分算法相结合并进行了优化设计。对补零算法和差分相干积分算法进行了改进,将差分延迟时间调整为20ms,有效消除了NH码的影响,并增加了积分时间,提高了信噪比。采用Monte Carlo仿真测试了在载噪比为20dBHz~38dBHz的条件下,此算法与传统算法的检测性能。结果表明,相比传统算法,此算法的捕获灵敏度提高了约10dB。此算法能够有效消除北斗NH码相位变化对信号捕获的影响,并提高信噪比,适用于弱信号条件下的北斗信号捕获。     

基于周期Wigner-Hough变换多相编码连续波雷达信号检测算法

为提高雷达侦察截获接收机对多相编码连续波弱信号截获能力,提出了一种基于周期Wigner-Hough变换（Periodic Wigner-Hough Transform,PWHT）的多相编码连续波信号检测算法。研究了线性调频连续波信号的PWHT及性质;分析了多相编码连续波信号时频主脊线的类似线性调频连续波特征;推导了高斯白噪声在PWHT域的统计分布特征,根据多相编码连续波信号与线性调频连续波的相似性,提出了基于PWHT的多相编码连续波信号检测算法,给出了实现流程,并计算出其检测性能和参数估计性能仿真的仿真结果。仿真结果表明：该算法较已有的其他多相编码信号检测算法有更好的弱信号检测能力,最小可检测信噪比至少可以降低3dB,并随着观测时间延长而进一步降低;其参数估计精度具有渐进最优的性质。     

基于FRFT和相位差分算法的信号特征提取

基于分数阶傅里叶变换(Fractional Fourier Transform,FRFT)算法的信号识别方法已广泛应用于雷达信号处理领域,相位差分算法对于检测相位编码信号尤为高效。基于 FRFT和相位差分法的信号检测算法已被提出,但在较低的信噪比下该算法并不能准确识别 LFM、LFM-BPSK信号。针对低信噪比背景下该算法性能较差的问题,给出 1种改进的算法,并通过加入多相编码信号的识别,扩大其适用范围。仿真验证结果表明,提出的算法不仅较原有算法能在较低信噪比条件下有效检测 LFM、BPSK、Frank3种单一调制方式的信号,还能检测出复杂调制的 LFM-BPSK信号。     

基于均匀性判定规则的统计MIMO雷达多通道融合检测技术

针对统计MIMO雷达各观测通道统计特性不一致的情况,提出了一种多通道融合检测技术。该技术利用均匀性判定规则,选择一组均匀的、"被认为是具有较高信杂噪比"的局部检验统计量来构建全局检验统计量,即新的检测器。给出了新检测器的设计步骤和均匀性判定规则,并利用全概率公式证明了新检测器的虚警概率与每一操作步骤中过门限概率的关系,从而为仿真得出检测门限提供了理论基础。仿真结果表明,在不同通道间信噪比分布类型条件下,新检测器的检测性能具有较强的稳健性,且与不同条件下性能最优的检测器相比,其性能损失很小。     

Lognormal杂波环境中基于Hough变换的目标检测

给出了基于Hough变换的信号检测结构,推导了Lognormal分布杂波背景下基于Hough 变换检测器的检测性能的解析表达式,设计了具体的仿真环境和仿真流程,对基于Hough变换检测器在非起伏目标和四种Swerling起伏环境下的目标检测性能进行了分析。     

基于小波包分解和滑动功率谱的舰船轴频电场信号检测

轴频电场是可在水下探测到的一种运动舰船特征物理场,由于海水的衰减作用,其信号十分微弱。文章提出了一种基于小波包分解和滑动功率谱的微弱舰船轴频电场信号检测方法。首先,利用小波包变换对观测信号进行多子带分解;然后,分别提取各子带信号功率作为检测特征量,使用浮动门限对其进行滑动检测。实测数据和仿真数据处理表明,该方法能够在较低的信噪比条件下有效工作,性能优于传统的功率谱检测方法。     

基于独立成分分析的混合LFM信号检测

混合LFM信号广泛存在于实际信号环境巾,对其检测极其重要。对有严重交叉项的混合LFM信号的检测十分困难,因此提出了一种基于独立成分分析的混合LFM信号检测法。通过盲源分离提取各独立成分,利用时频分布矩阵的联合对角化法抑制交叉项,再由各成分信号自项求和重构Wigner-Ville分布,采用Wigner-Hough检测各LFM成分。分析了Wigner-Hough变换输入信噪比和输出信噪比的关系,仿真验证了算法的有效性,得出随着样本点数的增加,在低信噪比条件下,能获得好的检测性能的结论：     

一种提高脉冲雷达多普勒相位精度的方法

针对低信噪比条件下脉冲雷达模糊多普勒相位精度较低,可能导致相位测距时不能正确解相位模糊问题,基于EMD（Empirical Mode Decomposition,经验模式分解）区间阈值去噪方法,提出了一种新的提高多普勒相位精度的方法：利用EMD分解后各层信号的频率特性和能量特性,选取合适的阈值,并对各层信号进行区间阈值化处理,在提高信号信噪比的同时保持了信号的连续性.分别在回波信号噪声为高斯白噪声和AR（2）相关噪声的情况下,以及不同信噪比条件下,对该方法进行验证.仿真结果表明：在低信噪比条件下,当回波信号噪声为白噪声和相关噪声时,EMD区间阈值去噪方法能将回波信号信噪比提高5 dB,去噪性能优于小波阈值去噪方法,其对应多普勒相位精度能提高1倍以上.     

Adaptive polarimetric target detection with coherent radar. I.Detection against Gaussian background

The derivation of a completely adaptive polarimetric coherent scheme to detect a radar target against a Gaussian background is presented. A previously proposed Generalized Likelihood Ratio Test (GLRT) polarimetric detector is extended to the case of a general number of channels; this exploits the polarimetric characteristics of the received radar echoes to improve the detection performance. Together with the fully adaptive scheme, a model-based detector is derived that has a lower estimation loss. A complete theoretical expression is derived for the detection performance of both proposed polarimetric detectors. They are shown to have Constant False Alarm Rate (CFAR) when operating against Gaussian clutter, but to be sensitive to deviations from the Gaussian statistic. The application to recorded radar data demonstrates the performance improvement achievable in practice     

Adaptive polarimetric target detection with coherent radar. II.Detection against non-Gaussian background

For pt. I see ibid., vol. 37, no. 4, pp. 1194-1206 (2001).This paper presents the derivation of a polarimetric coherent adaptive scheme to detect a radar target against a non-Gaussian background. This completes the results presented in Part I for the Gaussian background. A Texture Free-Generalized Likelihood Ratio Test (TF-GLRT) detector is derived that exploits the polarimetric characteristics of the received radar echoes to improve the detection performance. The proposed polarimetric detector is shown to have Constant False Alarm Rate (CFAR) when operating against compound-Gaussian clutter with unknown parameters. Its performance is fully characterized by both theoretical analysis and simulation. Moreover, the application to recorded radar data demonstrates the performance improvement achievable in practice     

基于导航雷达实测数据的CFAR检测算法分析

为提高导航雷达在复杂环境中的目标检测能力,研究了修正中值(MMD)检测器在导航雷达中的应用,并与经典非参量广义符号(GS)检测器和参量最小选择(SO)检测器的检测结果进行对比。仿真结果表明:GS检测器对海上单一目标有较好的检测性能,但是在多目标环境下的检测性能严重下降;SO检测器虽然对上述环境有较好的检测性能,但是由于杂波包络分布类型难以准确已知,杂波抑制能力较差;MMD检测器在多目标环境下有较好的检测性能和杂波抑制能力。     

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.     

Spatial adaptive subspace detection in OTH radar

The work presented here addresses the problem of target detection against spatially structured interference composed of jamming plus noise, where for practical reasons, the received target wavefront may also deviate from the traditional plane wave model. This detection problem arises in over-the-horizon (OTH) radar systems where spatially distributed targets often compete for detection against directional interference that is spread over the entire range-Doppler search space. Conventional detection processing schemes are compared with a recently proposed adaptive subspace detector (ASD) that takes both the spatial structure of the interference and the possibility of target wavefront distortions into account. Experimental array data recorded by the Jindalee sky-wave and Iluka surface-wave OTH radar systems, located in central and northern Australia respectively, is used to evaluate detection performance.     

Performance of a Two-Sample Mann-Whitney Nonparametric Detector in a Radar Application

The detection of signals in an unknown, typically non-Gaussian noise environment, while attempting to maintain a constant false-alarm rate, is a common problem in radar and sonar. The raw receiver data is commonly processed initially by a bank of frequency filters. The further processing of the outputs from the filter bank by a two-sample Mann-Whitney detector is considered. When the noise statistics in all filters are identical, the Mann-Whitney detector is distribution free, i. e., the false-alarm probability may be prescribed in advance regardless of the precise form of the noise statistics. The primary purpose of this paper is to demonstrate the potential advantage of nonparametric detectors over conventional detectors. The signal detection performance of the Mann-Whitney detector is compared to that of an ordinary linear envelope detector plus integrator in the presence of Gaussian and several hypothetical forms of non-Gaussian noise. This comparison is made for both uniform and nonuniform distributions of noise power across the filter bank. Besides providing a much more constant false-alarm rate than the conventional detector, the Mann-Whitney detector's signal detection performance is found also to be much less sensitive to the form of the noise statistics. In one case, its detection sensitivity is found to be 11 dB better than that of the conventional detector. Even when the noise power density is made moderately nonuniform across the filter bank, the detection performance of the Mann-Whitney detector is found not to be significantly affected.     

Data Quantization for Narrowband Signal Detection

In automatic radar detection, digital integration of the envelope detector outputs is often used as a good approximation to the optimum. This requires quantizing the envelope detector outputs. In this paper, quantizer structures for narrowband signal detection are considered. Quantizer characteristics are derived to optimize performance as measured by the detector efficacy?an asymptotic performance measure. Asymptotic and finite sample performance results are presented. The results obtained are not limited in their application to Gaussian noise only, although this important case is given specific consideration.     

Studies of target detection algorithms that use polarimetric radardata

Algorithms are described which make use of polarimetric radar information in the detection and discrimination of targets in a ground clutter background. The optimal polarimetric detector (OPD) is derived. This algorithm processes the complete polarization scattering matrix (PSM) and provides the best possible detection performance from polarimetric radar data. Also derived is the best linear polarimetric detector, the polarimetric matched filter (PMF), and the structure of this detector is related to simple polarimetric target types. New polarimetric target and clutter models are described and used to predict the performance of the OPD and the PME. The performance of these algorithms is compared with that of simpler detectors that use only amplitude information to detect targets. The ability to discriminate between target types by exploring differences in polarimetric properties is discussed     

无需辅助数据的分布式目标自适应检测器

在非高斯背景和没有辅助数据的条件下,研究了高分辨率雷达分布式目标的自适应检测问题.首先采用有序检测理论和协方差矩阵的迭代估计方法粗略估计散射点集合,进一步利用迭代估计方法获得协方差矩阵的近似最大似然估计,提出了无需辅助数据的自适应检测器(ADWSD).ADWSD在非高斯背景下具有近似恒虚警率特性,且检测性能远好于修正的...