Passive infrared detector used for detection of very slowly moving of crawling people

The paper presents construction and principle of operation of passive IR detectors (PIR detectors) of a large detection range. Important virtue of these detectors is highly efficient detection of slowly moving or crawling people. The described here PIR detector detects crawling people at the distance of 140 m. To ensure high probability of detection of slowly moving objects, new method of signals analysis was applied. On the basis of the carried out real-time measurements, both probability of detection and false alarms were determined.     

Heterodyne detection enhanced by quantum correlation

Heterodyne detectors as phase-insensitive(PI) devices have found important applications in precision measurements such as space-based gravitational-wave(GW) observation. However, the output signal of a PI heterodyne detector is supposed to suffer from signal-to-noise ratio(SNR) degradation due to image band vacuum and imperfect quantum efficiency. Here, we show that the SNR degradation can be overcome when the image band vacuum is quantum correlated with the input signal.We calculate the noise figure of the detector and prove the feasibility of heterodyne detection with enhanced noise performance through quantum correlation. This work should be of great interest to ongoing space-borne GW signal searching experiments.     

变分模态分量降噪后重构的水声弱信号检测

针对能量检测法在低信噪比下对非合作水声探测信号的检测性能显著下降的问题,提出了一种组合变分模态分解和小波变换降噪重构的信号检测方法。以信号分解出的各个本征模态函数的近似熵与互相关系数比值作为分量分类参数,将所得分量分为信号分量、含噪信号分量与噪声分量,然后利用第二代小波变换对含噪信号分量降噪后与信号分量组成重构信号,最后对重构信号进行检测。数值仿真结果表明该方法可以在无先验信息的情况下对CW和LFM信号自适应降噪,信噪比0 dB以下时CW信号重构后信噪比提升约12 dB,宽带LFM信号信噪比提升约8～9 dB,有效提升了低虚警概率下信号的检测概率。湖试结果表明,虚警概率为0.1时检测概率可提升至0.9以上,验证了该方法的有效性。     

Acoustic detection and classification of river boats

We present a robust algorithm to detect the arrival of a boat of a certain type when other background noises are present. It is done via the analysis of its acoustic signature against an existing database of recorded and processed acoustic signals. We characterize the signals by the distribution of their energies among blocks of wavelet packet coefficients. To derive the acoustic signature of the boat of interest, we use the Best Discriminant Basis method. The decision is made by combining the answers from the Linear Discriminant Analysis (LDA) classifier and from the Classification and Regression Trees (CART) that is also accompanied with an additional unit, called Aisles, that reduces false alarms rate. The proposed algorithm is a generic solution for process control that is based on a learning phase (training) followed by an automatic real time detection while minimizing the false alarms rate.     

Stochastic analysis of recurrence plots with applications to the detection of deterministic signals

Recurrence plots have been widely used for a variety of purposes such as analyzing dynamical systems, denoising, as well as detection of deterministic signals embedded in noise. Though it has been postulated previously that recurrence plots contain time correlation information here we make the relationship between unthresholded recurrence plots and the covariance of a random process more precise. Computations using examples from harmonic processes, autoregressive models, and outputs from nonlinear systems are shown to illustrate this relationship. Finally, the use of recurrence plots for detection of deterministic signals in the presence of noise is investigated and compared to traditional signal detection methods based on the likelihood ratio test. Results using simulated data show that detectors based on certain statistics derived from recurrence plots are sub-optimal when compared to well-known detectors based on the likelihood ratio.     

Background noise cancellation for improved acoustic detection of manatee vocalizations

The West Indian manatee (Trichechus manatus latirostris) has become endangered partly because of an increase in the number of collisions with boats. A device to alert boaters of the presence of manatees, so that a collision can be avoided, is desired. A practical implementation of the technology is dependent on the hydrophone spacing and range of detection. These parameters are primarily dependent on the manatee vocalization strength, the decay of the signal's strength with distance, and the background noise levels. An efficient method to extend the detection range by using background noise cancellation is proposed in this paper. An adaptive line enhancer (ALE) that can detect and track narrow band signals buried in broadband noise is implemented to cancel the background noise. The results indicate that the ALE algorithm can efficiently extract the manatee calls from the background noise. The improved signal-to-noise ratio of the signal can be used to extend the range of detection of manatee vocalizations and reduce the false alarm and missing detection rate in their natural habitat.     

Comparison between visual and passive acoustic detection of finless porpoises in the Yangtze River, China

Recently, sonar signals and other sounds produced by cetaceans have been used for acoustic detection of individuals and groups in the wild. However, the detection probability ascertained by concomitant visual survey has not been demonstrated extensively. The finless porpoises (Neophocaena phocaenoides) have narrow band and high-frequency sonar signals, which are distinctive from background noises. Underwater sound monitoring with hydrophones (B&K8103) placed along the sides of a research vessel, concurrent with visual observations was conducted in the Yangtze River from Wuhan to Poyang Lake in 1998 in China. The peak to peak detection threshold was set at 133 dB re 1 ,EPa. With this threshold level, porpoises could be detected reliably within 300 m of the hydrophone. In a total of 774-km cruise, 588 finless porpoises were sighted by visual observation and 44 ,864 ultrasonic pulses were recorded by the acoustical observation system. The acoustic monitoring system could detect the presence of the finless porpoises 82% of the time. A false alarm in the system occurred with a frequency of 0.9%. The high-frequency acoustical observation is suggested as an effective method for field surveys of small cetaceans, which produce high-frequency sonar signals.     

次声信号的时频信号能量统计检测方法

次声信号检测是次声事件监测的重要环节,常用的短时平均与长时平均之比STA/LTA(Short Term Average to Long Term Average)和著名的逐次多通道互相关方法PMCC(the Progressive Multiple Cross-Correlation)误检率都比较高.为此,提出一种时频域信号能量统计的次声信号检测方法,其基本原理是根据目标信号与噪声的频域分布差异,采用窄带分频技术将待检波形变换到时频域,按时频格点计算局部平均能量与全局平均能量之比,当比值大于设定阈值时,认为该格点属于目标信号的一部分。以国际监测系统次声台站监测数据为对象进行了实验研究,并与PMCC检测结果进行了比较,结果表明所提出的信号检测方法对微弱次声信号检测能力强、误检信号少.      

Miniature array postdetection-encoded MRI

A method for performing nuclear magnetic resonance (NMR) measurements simultaneously from more than a single radiofrequency (RF) coil is presented. The method employs the detection of magnetic resonance signals in an array of detectors, where each detector is responsible for detecting a unique frequency bandwidth or a magnetic resonance signal from a unique location in a region in a primary, substantially homogeneous, static magnetic field. The detectors may be separated logically into groups, whereby all the detectors in a given group are essentially RF-decoupled from each other to substantially eliminate cross-talk by switching circuits or by being placed from each other sufficiently remotely. Sampling of detected signals from detectors in this array is done simultaneously over groups of noninteracting detectors. The detected signals from all detectors in a given group are simultaneously transmitted to a single preamplifier, thus increasing significantly the signal-to-noise ratio (SNR) in that preamplifier. Prior to transmitting each detected NMR signal of each detector to the preamplifier, each detected signal is separately and uniquely encoded electronically. This provides a method whereby the signal of each detector is uniquely encoded. Accumulating all these encoded signals, which were simultaneously received in a number of RF detectors into a single amplifier, results in the total signal having a high SNR ratio. This total amplified signal is later decoded into each detector's original signal by a decoding circuitry. Conventional magnetic resonance imaging (MRI) techniques may be thereafter applied to obtain an image. Or else, conventional NMR techniques may be thereafter applied to obtain an improved SNR from a sample, using a single preamplifier with a multitude of detectors. Applying this method to a large number of miniature and closely packed RF detectors placed in an array-like configuration results in an MRI technique with a very fast acquisition time, an increased SNR and a high spatial resolution equivalent to the number of detectors per unit of length. Deblurring and decoupling algorithms allow for images from layers as deep as 6 mm to be acquired.     

Detection of noise signals in multichannel reception under the conditions of parametrica priori uncertainty

The method of maximum likelihood is used to construct tests with a fixed probability of a false alarm, the powers of which do not depend on the unknown intensities of the signal and interference and the position of the signal but are determined only by the signal-to-noise ratio. The asymptotic statistical distribution in the absence of a signal is found, on which a detector of a weak noise signal is based. The constructed detectors are compared with known detectors by means of statistical simulation on a computer.Institute of Marine Transport Engineers. Scientific-Research Radiophysics Institute. Translated from Izvestiya Vysshikh Uchebnykh Zavedenii, Radiofizika, Vol. 37, No. 12, pp. 1546–1558, December, 1994.     

水下蛙人被动探测测向实验研究

为了对携带开式呼吸器的水下蛙人进行被动探测,本文采用四个水听器组成的十字阵在浅海水域对水下开式蛙人进行了被动探测、测向实验。结果表明:蛙人辐射噪声具有周期性特征,其周期与蛙人的呼吸频率有关;另外,蛙人呼吸辐射噪声具有显著频带,并且其频带与蛙人携带的呼吸器有关。根据蛙人辐射噪声的显著频带和周期性特征,设计信号处理算法实现了对蛙人的被动声学探测识别。使用互相关方法处理一对水听器的接收信号,可以确定蛙人的方位,但是根据理论分析会出现一个假方位。对比十字阵中两对水听器的测向结果可确定蛙人的准确方位。     

Two Phenomena in Forward Scattering Experiments

Recent processing of earlier obtained experimental data has revealed two phenomena making it possible to obtain necessary and sufficient conditions for detecting a forward scattering signal with the best efficiency. The location object should intersect one of the rays connecting the emitter and the receiver without touching the water surface. This is the basis of the first phenomenon: significant (more than 100-fold) compression of the detected signal. The second phenomenon is that the noise background surrounding the detected signal is a type of noise formed by an uneven bottom relief. This noise does not generate false alarms and is physically similar to speckle noise in optics. It is demonstrated that additive noise is primarily formed by signals scattered by a rough lake surface and that this noise is weakly suppressed when detecting the useful signal; however, it can be eliminated by imparting directivity to the illuminating signal source. All other noise is completely suppressed.     

参数未知的舰船辐射噪声检测方法

舰船辐射噪声的检测方法已有广泛研究,其中线谱特征是检测的重要依据。基于线谱特征的舰船辐射噪声检测方法常需要线谱数目、频率等参数作为检测的先验信息,这些信息不准确或无法确知时,检测方法的性能会受到显著影响。针对实际应用中对于未知舰船无法获得其参数信息的情况,研究基于连续谱谱峰特征的更为一般性的信号存在性检测方法。将窄带信号瞬时频率分析的思想扩展到舰船辐射噪声这类宽带信号,从信号频率与能量分布的角度推导得到宽带信号"瞬时频率"的近似表示式。构建宽带信号的瞬时频率检测器,并对其性能进行理论分析,结果表明该检测器的性能主要受舰船辐射噪声瞬时频率方差以及接收信噪比影响。通过计算机仿真和实际数据对算法的性能进行了验证。      

基于光谱吸收原则的低成本硫化氢传感器研究

H₂S浓度检测的发展趋势是实时检测,基于光谱吸收原则是其中一个发展方向。用宽带光源替代以往使用的成本较高的窄带光源,降低整个系统的成本,可以提高检测系统的实用性。宽带光源经过Bragg光纤光栅滤波后可以得到窄带光。此方法得到的光波必然会有噪声和波动,然后对其进行滤波,消除一部分系统的噪声和波动,再通过光线分束器分别通入检测光路和参考光路后做差。此差分信号不仅消除了一部分系统噪声和波动,还消除了基波分量,增大了信噪比。用数学分析的方法推导出二次谐波信号,利用SIMILINK仿真观察此信号,不同浓度的H₂S气体会有不同的输出信号,也就得到了气体的浓度。双光路差分法、谐波检测技术和窄带滤波技术综合起来的优势是降低了成本,增加了信噪比,提高了系统的检测能力。实验仿真结果表明,在LED宽带光源基础上采用提取谐波信号的双光路差分方法检测H₂S气体浓度正确可行,此方法降低了系统成本,为大范围实际应用提供了可能性。     

Leak Detection of Gas Pipelines Based on Characteristics of Acoustic Leakage and Interfering Signals

When acoustic method is used in leak detection for natural gas pipelines, the external interferences including operation of compressor and valve, pipeline knocking, etc., should be distinguished with acoustic leakage signals to improve the accuracy and reduce false alarms. In this paper, the technologies of extracting characteristics of acoustic signals were summarized. The acoustic leakage signals and interfering signals were measured by experiments and the characteristics of time-domain, frequency-domain and time-frequency domain were extracted. The main characteristics of time-domain are mean value, root mean square value, kurtosis, skewness and correlation function, etc. The features in frequency domain were obtained by frequency spectrum analysis and power spectrum density, while time-frequency analysis was accomplished by short time Fourier transform. The results show that the external interferences can be removed effectively by the characteristics of time domain, frequency domain and time-frequency domain. It can be drawn that the acoustic leak detection method can be applied to natural gas pipelines and the characteristics can help reduce false alarms and missing alarms.     

Adaptive window-length detection of underwater transients using wavelets

This paper describes a detection method that adapts to unknown characteristics of the underlying transient signal, such as location, length, and time-frequency content. It applies a set of embedded detectors tuned to a number of signal partitions. The detectors are based on the wavelet theory, whereby two different techniques are examined, one using local Fourier transform and the other using discrete wavelet transform. The detection statistics are computed so as to enable prewhitening of unknown colored noise and to allow for a constant false-alarm rate detection. An adapted segmentation of the signal is next obtained with a goal of finding the largest detection statistics within each segment of the partition. The detectors are tested using several underwater acoustic transient signals buried in ambient sea noise.     

A generalized power-law detection algorithm for humpback whale vocalizations

Conventional detection of humpback vocalizations is often based on frequency summation of band-limited spectrograms under the assumption that energy (square of the Fourier amplitude) is the appropriate metric. Power-law detectors allow for a higher power of the Fourier amplitude, appropriate when the signal occupies a limited but unknown subset of these frequencies. Shipping noise is non-stationary and colored and problematic for many marine mammal detection algorithms. Modifications to the standard power-law form are introduced to minimize the effects of this noise. These same modifications also allow for a fixed detection threshold, applicable to broadly varying ocean acoustic environments. The detection algorithm is general enough to detect all types of humpback vocalizations. Tests presented in this paper show this algorithm matches human detection performance with an acceptably small probability of false alarms (P(FA) < 6%) for even the noisiest environments. The detector outperforms energy detection techniques, providing a probability of detection P(D) = 95% for P(FA) < 5% for three acoustic deployments, compared to P(FA) > 40% for two energy-based techniques. The generalized power-law detector also can be used for basic parameter estimation and can be adapted for other types of transient sounds.     

Development and comparison of spectral methods for passive acoustic anomaly detection in nuclear power plants

We have developed spectral signal processing methods for passive acoustic anomaly detection in nuclear power plants. Furthermore, we compared the developed and existing methods by applying them to stationary sounds recorded in a controlled environment. Our new methods show significant improvement, in particular concerning robustness against false alarms. The results also demonstrate that clear detection of a given sound at a given signal-to-noise ratio is highly dependent on the distribution of characteristic frequency content in the spectrum in relation to the background noise and the spectral uncertainty. Since the frequency monitoring principle used here is quite rigid, we stress the need for research on more flexible methods, also taking into account differences between experiments and real reactor systems.     

Principal component analysis for emergent acoustic signal detection with supporting simulation results

A method is introduced that uses principal component analysis (PCA) to detect emergent acoustic signals. Emergent signal detection is frequently used in radar applications to detect signals of interest in background clutter and in cognitive radio to detect the primary user in a frequency band. The method presented differs from other standard techniques in that the detection of the signal of interest is accomplished by detecting a change in the covariance between two channels of data instead of detecting the change in statistics of a single channel of data. For this paper, PCA is able to detect emergent acoustic signals by detecting when there is a change in the eigenvalue subspace of the covariance matrix caused by the addition of the signal of interest. The algorithm's performance is compared to an energy detector and the Neyman-Pearson theorem. Acoustic simulations were used to verify the performance of the algorithm. Simulations were also used to examine the effectiveness of the algorithm under various signal-to-interferer and signal-to-noise ratios, and using various test signals.     

A Novel Blind Signal Detector Based on the Entropy of the Power Spectrum Subband Energy Ratio

In this paper, we present a novel blind signal detector based on the entropy of the power spectrum subband energy ratio (PSER), the detection performance of which is significantly better than that of the classical energy detector. This detector is a full power spectrum detection method, and does not require the noise variance or prior information about the signal to be detected. According to the analysis of the statistical characteristics of the power spectrum subband energy ratio, this paper proposes concepts such as interval probability, interval entropy, sample entropy, joint interval entropy, PSER entropy, and sample entropy variance. Based on the multinomial distribution, in this paper the formulas for calculating the PSER entropy and the variance of sample entropy in the case of pure noise are derived. Based on the mixture multinomial distribution, the formulas for calculating the PSER entropy and the variance of sample entropy in the case of the signals mixed with noise are also derived. Under the constant false alarm strategy, the detector based on the entropy of the power spectrum subband energy ratio is derived. The experimental results for the primary signal detection are consistent with the theoretical calculation results, which proves that the detection method is correct.