Multiband coherent radar detection against compound-Gaussianclutter

A Multiband GLRT-LQ (Generalized Likelihood Ratio Test-Linear Quadratic), MBGLRT-LQ, detector is derived for the coherent radar target detection against a compound-Gaussian clutter background. This scheme is an extension to the multiband case of the Asymptotically Optimum Detector (AOD), also derived under the name of GLRT-LQ in. The proposed multiband version of the algorithm shows two main advantages with respect to the original single-band algorithm. 1) For the adaptive implementation, it requires a much smaller area of homogeneous clutter echoes to estimate the covariance matrix of the interference; 2) it provides an optimum processing of the radar echoes when the radar operates in frequency agility, as electronic counter-countermeasure (ECCM) strategy. A closed form performance analysis is provided for the MBGLRT-LQ detector, which is used to compare it with the single-band version. An application to live recorded data is also presented to validate the obtained results     

A persymmetric multiband GLR algorithm

By exploring the covariance structure information to reduce the uncertainty in adaptive processing, a persymmetric generalized likelihood ratio algorithm (PGLR) is developed together with the closed-form expressions of probabilities of detection and false alarm. This multiband algorithm, which requires less computation, can significantly outperform the corresponding unstructured multiband GLR algorithm, especially in a severely nonstationary and/or nonhomogeneous interference environment. Simulation shows that the constant false alarm rate (CFAR) performance of the new algorithm is as insensitive as that of the unstructured multiband GLR to the departure of interference distribution from Gaussian     

On adaptive multiband signal detection with the SMI algorithm

In a nonstationary and/or nonhomogeneous interference environment, an adaptive system for target detection may suffer a severe performance degradation due to the lack of a sufficient amount of data from which the system can learn (estimate) the statistics of the environment. The detection performance of an adaptive system, which employs a frequency diversity (multiband) signaling waveform and a multiband sample matrix inversion algorithm (SMI), is analyzed. By comparison with the corresponding single-band system under the chosen system constraint, it is shown that the multiband system can significantly outperform the single band when the amount of data available from a single frequency band is severely limited by the environment     

An adaptive array detector with mismatched signal rejection

An adaptive detection algorithm with a sensibility parameter for rejecting unwanted signals is presented. This algorithm is a simple modification of the generalized likelihood ratio (GLR) detector (or test) for detecting a signal in zero mean Gaussian noise with unknown correlation matrix. Specifically, the adaptive detection algorithm is obtained by introducing an arbitrary positive scalar, which is called the sensitivity parameter, into the GLR detector as a multiplier of an already existing quadratic term. The GLR detector then becomes a special case of this detector for the unity sensitivity parameter. It is shown that the sensitivity parameter controls the degree to which unwanted signals are rejected. From numerical examples, it is demonstrated how the sensitivity parameter can be chosen such that unwanted signals, can be rejected while maintaining acceptable detection loss for slightly mismatched signals. Further insight into previous work on adaptive detection is also given     

Target detection with synthetic aperture radar

Target detection with synthetic aperture radar (SAR) is considered. We derive generalized likelihood ratio (GLR) detection algorithms that may be used with SAR images that are obtained with coherent subtraction or have Gaussian distributions. We analytically compare the performance of (1) a single pixel detector, (2) a detector using complete knowledge of the target signature information and known orientation information, (3) a detector using incomplete knowledge of the target signature information and known orientation information (4) a detector using unknown target signature information and known orientation information, and (5) a detector using unknown target signature information and unknown orientation information     

Performance comparisons of modified SMI and GLR algorithms

Adaptive filtering for signal detection in colored interference of unknown statistics is addressed. The detection performance of a modified version of the well-known sample matrix inversion (SMI) algorithm, called the modified SMI (MSMI), is compared with that of the generalized likelihood ratio (GLR) algorithm in colored Gaussian interference. The performance sensitivity of the MSMI and GLR in colored Weibull and log-normal interference is studied via simulation. It is found that there is almost no need to use the more complicated GLR algorithm in Gaussian interference, while in Weibull or log-normal interference the GLR should be preferable to the MSMI     

Further results on adaptive filtering with embedded CFAR

Among the few known adaptive filtering algorithms which have an embedded (integrated) constant false alarm rate (CFAR) performance feature, the generalized likelihood ratio (GLR) test algorithm has been found to be robust in non-Gaussian clutter. This paper examines the detection performance of the GLR algorithm in nonhomogeneous/nonstationary clutter environments which lead to nonidentical distribution of secondary (training) data. For two common types of nonhomogeneity, i.e., the so-called “signal contamination” and “clutter edge”, the asymptotic detection performance is derived and compared with simulations. These asymptotic results are relatively simple to use and they predict the GLR performance in nonhomogeneous environments quite well. The GLR performance loss due to the nonhomogeneity is also evaluated. It is found that the “generalized angle” between the desired and contaminating signal plays an important role in the study of the effects of signal contamination. It is also found that the performance degradation due to the clutter edge depends largely on the width of the clutter spectrum and target-clutter Doppler separation     

Interrelationship of single-filter and multiple-model adaptivealgorithms

An equivalent filter bank structure for multiple model adaptive estimation (MMAE) is developed that uses the residual and state estimates from a single Kalman filter and linear transforms to produce equivalent residuals of a complete Kalman filter bank. The linear transforms, which are a function of the differences between the system models used by the various Kalman filters, are developed for modeling differences in the system input matrix, the output matrix, and the state transition matrix. The computational cost of this new structure is compared with the cost of the standard Kalman filter bank (SKFB) for each of these modeling differences. This structure is quite similar to the generalized likelihood ratio (GLR) structure, where the linear transforms can be used to compute the matched filters used in the GLR approach. This approach produces the best matched filters in the sense that they truly represent the time history of the residuals caused by a physically motivated failure model     

二元高超声速进气道不起动状态的信号特征及预警

 对高超声速进气道的不起动进行了研究,首先给出了某二元高超声速进气道由起动到不起动全过程的壁面压强信号历程,并利用短时傅里叶变换(STFT)和小波变换(WT)方法对不起动过程中壁面压强信号的时-频特性进行了分析,然后采用累积和(CUSUM)和最大似然比(GLR)变化检测算法,对高超声速进气道的喘振现象进行了预测。研究结果表明,高超声速进气道喘振发生时,壁面压强信号的时-频特性存在显著改变,能量谱密度(PSD)分布出现了有规律的集中,其基频在200～340 Hz范围,并随着堵塞度(TR)的增加而增加。另外,在喘振发生前,进气道收敛段的下壁面附近存在大尺度的分离包,其有规律的尺度变化和前后移动导致了明显的壁面压强脉动特征,因此可作为一种前兆来预测喘振现象的出现。在本文条件下,两种变化检测算法均可在大喘发生前约220 ms发出警报,表明了该喘振预警思路的可行性。     

低成本GNSS终端中北斗三号多频观测的分析及应用CSCD

低成本消费级GNSS芯片相较于传统测绘级接收机在体积、功耗等方面具有突出优势,在未来无人驾驶、物联网等新兴应用领域具有极大潜力。然而当前低成本GNSS芯片的观测量存在非常严重的噪声和误差,为了改善观测质量,低成本芯片正逐渐从单频向多频过渡。首先调研了目前低成本GNSS接收机对多频信号的支持情况,然后介绍了北斗三号多频观测在电离层延迟和整周模糊度估计等方面的应用。通过对真实数据的采集和分析,针对当前原始观测量存在的诸多问题,提出了具体的预处理方案,并在此基础上开展了信号强度、电离层和模糊度实验。实验结果表明,基于华为Mate 40手机的低成本GNSS方案的北斗三频电离层延迟估计误差的均值为-2.97m,三频整周模糊度估计的成功率达93.8%,相较于单频整周模糊度估计的3.11%成功率有显著提升。     

Design and characteristics of a multiband communication satelliteantenna system

Feasibility studies on a multiband communication satellite antenna system and the key technologies involved in devising this system are described. The proposed multiband communication satellite utilizes four frequency bands: Ka (30/20 GHz), Ku (14/12 GHz), C (6/4 GHz), and S (2.6/2.5 GHz). It has six beam configurations, three multibeam and three shaped-beam. The following key technologies are presented: (1) a low-loss frequency selective subreflector (FSR) for compact feeds, (2) a low-loss and broadband frequency selective surface (FSS), and (3) a highly accurate and reliable mesh reflector     

冗余配置捷联惯导系统故障检测门限的确定

以5个单敏感轴陀螺斜置式安装为例 ,讨论了当系统采用广义似然比方法进行故障检测时2个重门限值的设定 ,利用最小错误概率和系统最大可靠性2种指标对门限值进行了优化 ,并对这2种方法的适用范围和优化结果进行了讨论。     

光电池测光器在爆震波测量中的应用

爆震管内火焰的结构非常复杂且传播速度快,需要高精度、高响应时间的测试工具.本文在单爆震试验中采用光电池测光器和离子探针测量燃烧波.研究中以高频响压力传感器为参考依据,通过测量同一截面上压力传感器、光电池测光器和离子探针之间的触发顺序,以及光电池测光器与离子探针信号的持续时间,来验证光电池测光器在爆震波测量中的可行性与精度.结果表明:光电池测光器比离子探针更适合测量爆震管内火焰传播速度.      

先验失配条件下的知识辅助检测器稳健性分析

充分利用探测环境的先验信息是提高雷达探测能力的有效途径之一。先验信息必须在雷达检测算法设计阶段确定下来,因此先验信息与当前探测环境之间可能存在不一致性。以复合高斯杂波中的、利用纹理分量先验信息的知识辅助(KA)检测器作为研究对象,首先建立了该检测器检测性能与先验分布参数失配之间的量化关系,然后根据给定的杂波探测环境模型参数,分析了先验模型失配对检测性能的影响。分析结果表明:知识辅助检测器的稳健性与当前探测环境模型参数有关。进一步给出了先验模型失配的容许区间,当先验模型参数在这个区间内,知识辅助检测器性能优于不使用先验信息的检测器性能。     

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.     

A variably trimmed mean CFAR radar detector

A variably trimmed mean (VTM) constant false alarm rate (CFAR) detector in which the threshold is determined by processing a linear combination of a group of ordered samples in each window is introduced. Unlike the trimmed mean detector, the number of ordered samples that require further processing is allowed to vary according to a data-dependent rule. It is demonstrated that the VTM detector exhibits performance characteristics that are independent of the total (stationary) noise power. Simulated performance results are presented for regions of clutter power transitions and for multiple target environments to illustrate the possible improvement over the order-statistic detector that can be obtained by using a VTM detector     

Weak Signal Detection in Non-Gaussian Noise of Unknown Level

An adaptive threshold detector to test for the presence of a weak signal in additive non-Gaussian noise of unknown level is discussed. The detector consists of a locally optimum detector, a noise level estimator, and a decision device. The detection threshold is made adaptive according to the information provided by the noise level estimator in order to keep a fixed false-alarm probability. Asymptotic performance characteristics are obtained indicating relationships among the basic system parameters such as the reference noise sample size and the underlying noise statistics. It is shown that, as the reference noise sample size is made sufficiently large, the adaptive threshold detector attains the performance of a corresponding locally optimum detector for detecting the weak signal were the noise level known.     

The Detection Performance of a Modified Moving Window Detector

The modified moving window detector for binary integration has a shorter window length compared with the ordinary moving window detector because of the addition of a third threshold. When the second threshold is reached, a counter begins to count until the third threshold is reached. A graphical method using a probability chain is developed here to analyze and to calculate the detection performance of this type detector. The detection performances for some practical cases are calculated by computer and are compared with the ordinary moving window detector.     

Detection of long-duration narrowband processes

Detecting long, weak signals that are narrowband but of unknown frequency structure is an important signal processing challenge, with many applications in remote sensing and process monitoring. An ad hoc scheme is developed. Its stages include the discrete Fourier transform (DFT), a multiresolution decomposition in the frequency domain, and a generalized likelihood ratio test (GLRT). The computational load is light, and the performance is remarkably good. This is so not just in the original narrowband situation, but also, due to an inherent adaptivity to the data, in the detection of signals that are relatively broadband in nature. Generalizations are given to constant false alarm rate (CFAR) operation in both prewhitened and unwhitened cases, and to the detection of multiband signals. As regards the last, it is discovered that there is little loss from overestimating the number of bands     

PAM approach to weak CPM and its application to flight termination receivers

A method for computing the PAM representation for weak continuous phase modulation (CPM) is presented and applied to the modulation defined in the enhanced flight termination system (EFTS) standard. The pulse-amplitude modulation (PAM) representation was used to formulate a reduced-complexity detector whose performance is within 0.7 dB of maximum likelihood detection and 5.6 dB better than limiter-discriminator detection in the additive white Gaussian noise (AWGN) environment. The complexity of the reduced-complexity detector is less than 25% that of the maximum likelihood detector but, unlike the limiter-discriminator detector, requires a carrier phase PLL. In the presence of phase noise, the reduced-complexity detector outperforms limiter-discriminator detection when the RMS frequency deviation due to phase noise is less than 10% of the bit rate.