一种分布式双麦克风线阵声源定位方法

分布式麦克风阵列由于比传统的单阵列具有更大的空间孔径,可以获得更好的声源定位性能,因此基于分布式麦克风阵列的声源定位方法成为当前麦克风阵列领域研究的热点之一。本文研究了一种基于分布式双麦克风线阵的声源定位方法,并进行了系统实现,从理论上剖析了该算法的定位精度与单阵列定向误差以及声源位置之间的关系,而且还揭示了声源高度扰动对该算法定位精度的影响。最后,分别通过仿真实验和实际定位系统的测试结果,验证了本文理论分析的正确性。     

用垂直阵和单水听器测量水下目标辐射噪声的误差分析及其修正方法

文章给出了水声波导模型下垂直阵和单水听器测量水下目标辐射噪声的误差和修正方法,以便使两种测量结果一致和统一。在设定典型水声波导的参数后,用波数积分方法计算出声源到垂直阵各阵元的信道传输函数,再推导出垂直嵌套阵聚焦波束的信道传输函数,从而得到单水听器和垂直嵌套阵的测量误差。数值计算表明在70 m海深条件下,不同深度单水听器测量单频信号频谱级起伏达15 dB以上,总声级测量误差的均值为3 dB,而垂直嵌套阵测量单频信号频谱级起伏仅4 dB,总声级测量误差的均值趋于0 dB。海上实验测量单频信号声源级的结果与数值计算的起伏一致,海试中垂直阵获得较高的空间增益。结论是在浅海条件下垂直阵的测量精度高于单水听器的测量精度,用单水听器测量的目标总声级需要修正时可以修正,而用单水听器测量的单频信号声源级则难以修正。     

深海中利用单水听器的影区声源无源测距测深方法

在典型深海情况下当声源与接收水听器位于海水表层时,在影区内由声源海底接收器、声源海面海底接收器、声源海底海面接收器和声源海面海底海面接收器4条声线形成声场干涉结构,声强随着频率具有两种干涉周期,随着收发距离的增加而增大,分别随着声源深度、接收水听器深度的增加而减小。因此由单水听器记录的声场干涉结构即可实现宽带声源目标的无源测距测深,仿真分析验证了其有效性。在南海深海声学实验中观测到海面宽带噪声源在声场影区所形成的声场干涉结构,数据分析结果验证了深海声场干涉结构用于声源无源定位的有效性。与传统无源定位方法相比,该方法不需要宽带引导声源、精确的海底声学参数和大规模的拷贝场计算。      

单水听器波导不变量被动测距

本文主要讨论利用声场干涉现象由单水听器被动测距的可行性及测距性能,为此提出了单水听器波导不变量被动测距方法,通过提取LOFAR图上干涉条纹、使用简正波模型计算波导不变量、频域相关法估计相对速度,最后依据干涉条纹方程得到声源距离估计量。数值仿真和海上实验结果验证了单水听器被动测距的可行性,并具备一定测距性能,在3 dB信噪比环境中,对于7 km处的运动声源,平均测距误差小于5%。本文方法具有设备简单、易于推广至阵列信号处理等特点,为声纳信号处理环境宽容性的提高及环境适配声纳的设计开拓了思路。     

声学滑翔机联合的深海水下声源定位

为了验证多台滑翔机用于声源位置估计的可行性,提出了一种基于声学滑翔机的联合水下声源定位方法。首先利用水下滑翔机在东印度洋北部海域获取的声传播数据,分析了宽带脉冲信号的多途传播特性,然后提出了利用单水听器基于脉冲波形结构匹配的声源距离估计方法,在此基础上通过两台水下声学滑翔机联合定位的方式,实现了水下声源距离和方位的同步估计。结果表明:在印度洋深海非完全声道条件下,在100 km范围内,使用单台滑翔机估计的声源距离整体较为准确,但仍有估计误差较大点;联合两台滑翔机进行水下声源定位可进一步提高精度,对于200 m深度的声源,距离估计均方根误差为2.5 km,相对误差小于4%,方位估计均方根误差为2.4°。     

半经验关系与匹配场联合处理的爆炸声源快速定位

爆炸声源位置的快速准确获取对声源级测量和声传播计算具有重要意义。为了解决利用单一水听器进行爆炸声源定位时难以获得较好的定位效率和精度的问题,提出了一种基于半经验关系与匹配场联合处理的爆炸声源快速定位方法。首先通过爆炸声源满足的半经验关系,对爆炸位置进行预估,缩小匹配参数的搜索范围;同时,在基于多途时延差匹配定位理论的基础上,利用爆炸声源的半经验关系建立联合匹配定位方法,引入气泡脉动周期和冲击波峰值增加匹配物理信息,实现爆炸声源深度和距离精确反演。仿真分析与2013年南海水下爆炸声试验数据分析结果表明,一次气泡脉动周期与多途时延差的联合匹配可提高对爆炸声源深度的估计精度;冲击波峰值与多途时延差的联合匹配可提高对距离的估计精度。额外匹配量的引入减少了估计精度对接收阵元个数的依赖,能够实现用单阵元快速准确地进行爆炸源位置的估计。      

基于多阵列数据融合的宽带多声源定位研究

研究多个传声器阵列数据融合和宽带多声源近场定位算法。该算法首先融合多个传声器阵列数据,然后对多声源进行定位。由于充分利用多个阵列的数据,降低了分辨门限,提高了定位的精度和稳健性。通过仿真计算,证明了算法的有效性。     

基于声传播算子的声源定位实验模拟方法研究

声传播算子是一种高效的时域声场计算方法,它能够很方便地计算出给定系统参数下任意时刻任意位置的声场变化情况,本文采用这种方法计算所得的二维房间声场信息进行传声器阵列的声源定位仿真实验。计算结果表明,用该方法获取的阵列数据能有效地应用于阵列信号处理算法中,准确地估计出初始高斯脉冲声源的方向。声传播算子声场计算方法能为传声器阵列声源定位的实验提供方便,使得传声器阵列声源定位算法在不同混响时间的鲁棒性实验研究变得更加简捷。     

海洋声学环境下水中声源的时延估计法定位精度分析

水中声源的定位精度受到海洋声学环境的重要影响。结合海上试验的实际应用,分析了水下观测平台采用时延估计法对声源的定位精度问题。根据理论分析,计算了时延估计误差、海洋中声速不均匀、平台非稳性、及声传播起伏等因素引起的俯仰角和方位角误差。利用误差传递公式,获得了上述因素引起的不同平台深度下,不同距离声源的定位误差。比较了采用平面阵与立体阵、是否补偿声线弯曲效应等条件下定位误差的变化,并通过海上试验结果进行了部分验证。研究结果表明,海洋声速不均匀对定位误差的贡献最大。采用立体阵代替平面阵、测量海洋声速剖面并补偿声线弯曲引起的定位误差,在1000m距离上可使定位相对误差从最大30%降低到约10%,有效提高了较远距离上的定位精度。研究结果对于采取措施提高水中声源的定位精度有指导意义。      

一种改进的弹丸落点声学定位方法

研究了基于传感器阵列的声源定位技术,并在此基础上提出了一种改进的最小二乘声源定位方法。首先,根据风速、风向、温度对声速的影响,建立了观测值修正模型,再根据误差传播特性合理分配权阵,然后用最小二乘法进行定位解算;考虑观测值中可能含有粗差,将IGG3抗差模型加入到数据处理中,以提高系统的抗干扰能力;另外,通过观察残差向量,判断可能出现时序错误的观测值,再对时序不断调整,解决多声源时序混乱的问题。最后,通过对试验数据解算分析,证明本文方法的有效性和可行性。试验结果表明:改进的最小二乘声源定位方法可使定位误差达到4 m以下。本文所提方法不仅能有效降低粗差的影响,而且可准确处理多声源定位中观测值时序关系混乱的问题,可靠性较高。本文的研究内容紧密联系实际,可为声源定位设备的设计和应用提供参考依据。      

Source levels of clicks from free-ranging white-beaked dolphins (Lagenorhynchus albirostris Gray 1846) recorded in Icelandic waters

This study reports the source levels of clicks recorded from free-ranging white-beaked dolphins (Lagenorhynchus albirostris Gray 1846). A four-hydrophone array was used to obtain sound recordings. The hydrophone signals were digitized on-line and stored in a portable computer. An underwater video camera was used to visualize dolphins to help identify on-axis recordings. The range to a dolphin was calculated from differences in arrival times of clicks at the four hydrophones, allowing for calculations of source levels. Source levels in a single click train varied from 194 to 211 dB peak-to-peak (p-p) re: 1 microPa. The source levels varied linearly with the log of range. The maximum source levels recorded were 219 dB (p-p) re: 1 microPa.     

Who is whistling? Localizing and identifying phonating dolphins in captivity

Acoustic communication through whistles is well developed in dolphins. However, little is known on how dolphins are using whistles because localizing the sound source is not an easy task. In the present study, the hyperbola method was used to localize the sound source using a two-hydrophone array. A combined visual and acoustic method was used to determine the identity of the whistling dolphin. In an aquarium in Mexico City where two adult bottlenose dolphins were housed we recorded 946 whistles during 22 days. We found that a dolphin was located along the calculated hyperbola for 72.9% of the whistles, but only for 60.3% of the whistles could we determine the identity of the whistling dolphin. However, sometimes it was possible to use other cues to identify the whistling dolphin. It could be the animal that performed a behavior named “observation” at the time whistling occurred or, when a whistle was only recorded on one channel, the whistling dolphin could be the animal located closest to the hydrophone that captured the whistle. Using these cues, 15.4% of the whistles were further ascribed to either dolphin to obtain an overall identification efficiency of 75.7%. Our results show that a very simple and inexpensive acoustic setup can lead to a reasonable number of identifications of the captive whistling dolphin: this is the first study to report such a high rate of whistles identified to the free swimming, captive dolphin that produced them. Therefore, we have a data set with which we can investigate how dolphins are using whistles. This method can be applied in other aquaria where a small number of dolphins is housed; though, the actual efficiency of this method will depend on how often dolphins spend time next to each other and on the reverberation conditions of the pool.     

Echolocation signals of wild dolphins

Most of our understanding of dolphin echolocation has come from studies of captive dolphins performing various echolocation tasks. Recently, measurements of echolocation signals in the wild have expanded our understanding of the characteristics of these signals in a natural setting. Measuring undistorted dolphin echolocation signals with free swimming dolphins in the field can be a challenging task. A four hydrophone array arranged in a symmetrical star pattern was used to measure the echolocation signals of four species of dolphins in the wild. Echolocation signals of the following dolphins have been measured with the symmetrical star array: white-beaked dolphins in Iceland, Atlantic spotted dolphins in the Bahamas, killer whales in British Columbia, and dusky dolphins in New Zealand. There are many common features in the echolocation signals of the different species. Most of the signals had spectra that were bimodal: two peaks, one at low frequencies and another about an octave higher in frequency. The source level of the sonar transmission varies as a function of 20logR, suggesting a form of time-varying gain but on the transmitting end of the sonar process rather than the receiving end. The results of the field work call into question the issue of whether the signals used by captive dolphins may be shaped by the task they are required to perform rather than what they would do more naturally.     

Discriminating features of echolocation clicks of melon-headed whales (Peponocephala electra), bottlenose dolphins (Tursiops truncatus), and Gray's spinner dolphins (Stenella longirostris longirostris)

Spectral parameters were used to discriminate between echolocation clicks produced by three dolphin species at Palmyra Atoll: melon-headed whales (Peponocephala electra), bottlenose dolphins (Tursiops truncatus) and Gray's spinner dolphins (Stenella longirostris longirostris). Single species acoustic behavior during daytime observations was recorded with a towed hydrophone array sampling at 192 and 480 kHz. Additionally, an autonomous, bottom moored High-frequency Acoustic Recording Package (HARP) collected acoustic data with a sampling rate of 200 kHz. Melon-headed whale echolocation clicks had the lowest peak and center frequencies, spinner dolphins had the highest frequencies and bottlenose dolphins were nested in between these two species. Frequency differences were significant. Temporal parameters were not well suited for classification. Feature differences were enhanced by reducing variability within a set of single clicks by calculating mean spectra for groups of clicks. Median peak frequencies of averaged clicks (group size 50) of melon-headed whales ranged between 24.4 and 29.7 kHz, of bottlenose dolphins between 26.7 and 36.7 kHz, and of spinner dolphins between 33.8 and 36.0 kHz. Discriminant function analysis showed the ability to correctly discriminate between 93% of melon-headed whales, 75% of spinner dolphins and 54% of bottlenose dolphins.     

Beaked whale and dolphin tracking using a multichannel autonomous acoustic recorder

To track highly directional echolocation clicks from odontocetes, passive hydrophone arrays with small apertures can be used to receive the same high frequency click on each sensor. A four-hydrophone small-aperture array was coupled to an autonomous acoustic recorder and used for long-term tracking of high-frequency odontocete sounds. The instrument was deployed in the spring of 2009 offshore of southern California in a known beaked whale and dolphin habitat at about 1000 m depth. The array was configured as a tetrahedron with approximately 0.5 m sensor spacing. Time difference of arrival measurements between the six sensor-pairs were used to estimate three-dimensional bearings to sources. Both near-seafloor beaked whales and near-sea surface dolphins were tracked. The tracks observed using this technique provide swimming and diving behavioral information for free-ranging animals using a single instrument. Furthermore, animal detection ranges were derived, allowing for estimation of detection probability functions.     

An optical telemetry device to identify which dolphin produces a sound

A small telemetry device, called a "vocalight," was designed for attachment to a dolphin's head using a suction cup. The vocalight lights up a variable number of light-emitting diodes depending upon the loudness of sounds received at a hydrophone within the suction cup. If vocalights matched for sensitivity are put on each dolphin within a captive group, observers can identify which dolphin produces a vocalization. Use of vocalights indicates that source levels of whistles from captive bottlenosed dolphins, Tursiops truncatus, range from approximately 125 to over 140 dB re: 1 microPa at 1 m.     

Linking the sounds of dolphins to their locations and behavior using video and multichannel acoustic recordings

It is difficult to attribute underwater animal sounds to the individuals producing them. This paper presents a system developed to solve this problem for dolphins by linking acoustic locations of the sounds of captive bottlenose dolphins with an overhead video image. A time-delay beamforming algorithm localized dolphin sounds obtained from an array of hydrophones dispersed around a lagoon. The localized positions of vocalizing dolphins were projected onto video images. The performance of the system was measured for artificial calibration signals as well as for dolphin sounds. The performance of the system for calibration signals was analyzed in terms of acoustic localization error, video projection error, and combined acoustic localization and video error. The 95% confidence bounds for these were 1.5, 2.1, and 2.1 m, respectively. Performance of the system was analyzed for three types of dolphin sounds: echolocation clicks, whistles, and burst-pulsed sounds. The mean errors for these were 0.8, 1.3, and 1.3 m, respectively. The 95% confidence bound for all vocalizations was 2.8 m, roughly the length of an adult bottlenose dolphin. This system represents a significant advance for studying the function of vocalizations of marine animals in relation to their context, as the sounds can be identified to the vocalizing dolphin and linked to its concurrent behavior.     

Source levels and harmonic content of whistles in white-beaked dolphins (Lagenorhynchus albirostris)

Recordings of white-beaked dolphin whistles were made in Faxafl6i Bay (Iceland) using a three-hydrophone towed linear array. Signals from the hydrophones were routed through an amplifier to a lunch box computer on board the boat and digitized using a sample rate of 125 kHz per channel. Using this method more than 5000 whistles were recorded. All recordings were made in sea states 0-1 (Beaufort scale). Dolphins were located in a 2D horizontal plane by using the difference of arrival time to the three hydrophones, and source levels were estimated from these positions using two different methods (I and II). Forty-three whistles gave a reliable location for the vocalizing dolphin when using method II and of these 12 when using method I. Source level estimates on the center hydrophone were higher using method I [average source level 148 (rms) +/- 12 dB, n = 36] than for method II [average source level 139 (rms) +/- 12 dB, n = 36]. Using these rms values the maximum possible communication range for whistling dolphins given the local ambient noise conditions was then estimated. The maximum range was 10.5 km for a dolphin whistle with the highest source level (167 dB) and about 140 m for a whistle with the lowest source level (118 dB). Only two of the 43 whistles contained an unequal number of harmonics recorded at the three hydrophones judging from the spectrograms. Such signals could be used to calculate the directionality of whistles, but more recordings are necessary to describe the directionality of white-beaked dolphin whistles.     

Estimated communication range and energetic cost of bottlenose dolphin whistles in a tropical habitat

Bottlenose dolphins (Tursiops sp.) depend on frequency-modulated whistles for many aspects of their social behavior, including group cohesion and recognition of familiar individuals. Vocalization amplitude and frequency influences communication range and may be shaped by many ecological and physiological factors including energetic costs. Here, a calibrated GPS-synchronized hydrophone array was used to record the whistles of bottlenose dolphins in a tropical shallow-water environment with high ambient noise levels. Acoustic localization techniques were used to estimate the source levels and energy content of individual whistles. Bottlenose dolphins produced whistles with mean source levels of 146.7 ± 6.2 dB re. 1 μPa(RMS). These were lower than source levels estimated for a population inhabiting the quieter Moray Firth, indicating that dolphins do not necessarily compensate for the high noise levels found in noisy tropical habitats by increasing their source level. Combined with measured transmission loss and noise levels, these source levels provided estimated median communication ranges of 750 m and maximum communication ranges up to 5740 m. Whistles contained less than 17 mJ of acoustic energy, showing that the energetic cost of whistling is small compared to the high metabolic rate of these aquatic mammals, and unlikely to limit the vocal activity of toothed whales.     

单矢量水听器稀疏近似最小方差方位估计算法

针对单矢量水听器海上目标探测问题,利用稀疏近似最小方差(Sparse Asymptotic Minimum Variance,SAMV)算法进行目标方位估计,该算法利用单矢量水听器自身具有阵列流形的特点,将整个扫描空间离散化,目标方位分布于某一离散方向位置上,利用空间信号的稀疏性可提高目标方位估计性能。仿真结果表明,SAMV算法在各信噪比条件下方位估计噪声背景级明显优于常规波束形成(Conventional Beam Forming,CBF)算法和最小方差无失真响应(Minimum Variance Distortionless Response,MVDR)算法,当信噪比大于0dB时,该算法测向结果均方根误差小于2°,且SAMV算法具有更好的空间方位分辨能力。消声水池和海上声学浮标海上试验数据处理结果表明,SAMV算法给出了噪声背景级更低的目标方位历程图,有效验证了SAMV算法对海上目标的探测性能及其有效性。