Rajendar Bahl

Bio: Rajendar Bahl is an academic researcher from Indian Institute of Technology Delhi. The author has contributed to research in topics: Direction of arrival & Ganges River Dolphin. The author has an hindex of 11, co-authored 112 publications receiving 481 citations. Previous affiliations of Rajendar Bahl include Indian Institutes of Technology & University of Tokyo.

Marine vessel classification based on passive sonar data: the cepstrum-based approach

Abstract: Marine vessel classification is complicated by the variability in the radiated signal of the marine vessel because of changing machinery configuration for the same class of vessels. Further, the radiated signal of the marine vessel propagating towards a distant receiver undergoes random fluctuations in phase, amplitude and frequency. The ambient noise at the receiver will further complicate the authors’ classification problem. The shallow underwater channel, in particular, where these classification systems are more likely to operate presents the most challenges because of severe time-varying multi-path. Cepstral approaches are proposed in this study, including cepstral features and average cepstral features to augment existing feature sets that are mostly based on spectral analysis. Analytical studies have been supported by simulation experiments and tests on real ship recorded data. The cepstral features with cepstral liftering process is able to significantly reduce the multipath distortion effects of shallow underwater channel whereas the average cepstral feature is able to notably reduce the time-varying channel effects.

Diel changes in the movement patterns of Ganges River dolphins monitored using stationed stereo acoustic data loggers

Abstract: We monitored the underwater movements of Ganges River dolphins using stationed stereo acoustic data loggers. We estimated these movements using changes in the relative angle of the sound source direction (trajectory). Of the total acoustic recordings (66 h), 26.2% contained trajectories of dolphins, and 78.6% of these trajectories involved single animals, suggesting that dolphins tended to swim alone and were localized near the monitoring station. The observed trajectories were categorized as follows: staying type characterized by small changes in the sound source direction, moving type A (moving in the same direction), and moving type B (moving up and down the stream during recording). The average interpulse intervals of sounds in moving types A and B were significantly shorter than that of the staying type, suggesting that dolphins produce the former types of trajectories to echolocate across shorter distances during movement. The frequency of occurrence of moving type A increased during the night, whereas that of type B increased in the late afternoon and that of the staying type increased during the daytime. These results indicate that dolphins moving at night tended to use short-range echolocation, whereas during the day, they remained in relatively small areas and used long-range sonar.

Localization of sperm whales in a group using clicks received at two separated short baseline arrays.

Abstract: In this paper, a sperm whale click analysis scheme is proposed in order to calculate the position of individual sperm whales in a group using data received at two arrays deployed near the surface. The proposed method mainly consists of two parts: short baseline (SBL) with classification and long baseline (LBL) with class matching. In SBL with classification, a click is automatically detected, and its direction of arrival is calculated. The clicks are then classified based on their direction vectors. The class data are then sent together with direction data and matched to the other array’s class data. LBL with class matching is used for localization. The classification algorithm can be used to estimate the number of whales clicking and to list potential candidates for LBL matching. As a result, the proposed method is able to localize the positions of the whales in a group. The performance of the proposed method is evaluated using data recorded off Ogasawara islands with two arrays near the surface. The three-dimensional underwater trajectories of six sperm whales are extracted to demonstrate the capability of the proposed method.

Underwater behavioral study of Ganges river dolphins by using echolocation clicks recorded by 6-hydrophone array system

Abstract: Targeting the 9 Ganges river dolphins inhabiting the Narora area in Ganges river system, the first recordings using an compact acoustic observation system, which consists of a high frequency 6-hydorophone cross array connected with a PC on land-base by a wireless LAN system have been carried out during 17 to 21 February 2008. The system also uses the prototype of a GPRS modem-based real-time data transmission system to share the processed data with the world over the internet. The array structure consists of a horizontal cross array formed by 2 arms each of 1.6 meter length with a hydrophone on each corner and at the intersection forming two equi-spaced 3-hydrophone linear SBL system for omni-directional horizontal coverage, and one additional hydrophone which is fixed 0.8 meter below the center hydrophone of the cross array also forming an equi-spaced triangular SBL system for vertical measurement. The clicks of the dolphins received on each hydrophone were sampled at a rate of 500 kHz per channel. Total recording was done for approximately 40 hours due to power supply interruptions. However, the GPRS modem-based real-time data transmission system worked well during the recordings. The results of the basic analysis of the data show that the dolphins are found swimming up and down the river. The results are in accordance with the visual observation results. Underwater behavior of the dolphins approaching near to the array, which could not otherwise have been observed by visual survey, has been mainly analyzed in this paper. Based on ICI during this period of approaching to the array, we estimated ldquowhat this dolphin is seeingrdquo or interested in. We invoked the idea of lag time that the dolphin requires to perform echo-location process and to emit the next click to the target [7]. Defining the lag time as DeltaP (pre-click time) and assuming that DeltaP is constant, DeltaP and distance D to the target where the dolphin is looking at is calculated by using ICI and range between the dolphin and the array, which is measured by the array. Utilizing available on-axis clicks from the data of the preliminary experiments in Budhabalanga river, the value of DeltaP is calculated. Constant DeltaP is estimated as 14.3 milliseconds. To determine D of the Narora data, we applied it when the dolphin was approaching to the array within 20 meters. The results show that the dolphin does not look at any object beyond 20 meters range. On the other hand, when ICI reduced below the constant DeltaP (14.3 milliseconds) , it is estimated that the dolphin is in a different stage of the echo-location process.

Vocalization based Individual Classification of Humpback Whales using Support Vector Machine

Abstract: Visual surveys and DNA analysis hold primary importance in marine mammal observation. Especially, recognition of whales and their population density estimation rely heavily on these costly and tedious methods. Acoustic survey of vocalizing cetaceans, in contrast, is emerging as a promising technique for efficient, automatic, non-invasive and convenient observation and analysis of such vocally active organisms. However, it is, yet, too premature to replace the conventional methods altogether. In this paper, we have presented our results on recognition of individual humpback whales based on their vocalization data. Cepstral coefficients from song units extracted from audio records of seven humpback whales, re-sampled at 8KHz, were subjected to cepstral analysis. The extracted coefficients were used to develop multi-class support vector machine (SVM) classifier model. The test phase results indicated classification accuracy as high as 99% as compared to earlier best results of 88%, achieved by Gaussian mixture model (GMM) trained on cepstral coefficients. Furthermore, this improvement was attained with a highly reduced training dataset size. It was also verified that the song duration of approximately 128 seconds was sufficient for reliable identification in test phase for given dataset.

Regression Diagnostics: Identifying Influential Data and Sources of Collinearity

Abstract: 1. Introduction and Overview. 2. Detecting Influential Observations and Outliers. 3. Detecting and Assessing Collinearity. 4. Applications and Remedies. 5. Research Issues and Directions for Extensions. Bibliography. Author Index. Subject Index.

The state of the art in underwater acoustic telemetry

Abstract: Progress in underwater acoustic telemetry since 1982 is reviewed within a framework of six current research areas: (1) underwater channel physics, channel simulations, and measurements; (2) receiver structures; (3) diversity exploitation; (4) error control coding; (5) networked systems; and (6) alternative modulation strategies. Advances in each of these areas as well as perspectives on the future challenges facing them are presented. A primary thesis of this paper is that increased integration of high-fidelity channel models into ongoing underwater telemetry research is needed if the performance envelope (defined in terms of range, rate, and channel complexity) of underwater modems is to expand.

Acoustic monitoring in terrestrial environments using microphone arrays: applications, technological considerations and prospectus

Abstract: Summary 1. Animals produce sounds for diverse biological functions such as defending territories, attracting mates, deterring predators, navigation, finding food and maintaining contact with members of their social group. Biologists can take advantage of these acoustic behaviours to gain valuable insights into the spatial and temporal scales over which individuals and populations interact. Advances in bioacoustic technology, including the development of autonomous cabled and wireless recording arrays, permit data collection at multiple locations over time. These systems are transforming the way we study individuals and populations of animals and are leading to significant advances in our understandings of the complex interactions between animals and their habitats. 2. Here, we review questions that can be addressed using bioacoustic approaches, by providing a primer on technologies and approaches used to study animals at multiple organizational levels by ecologists, behaviourists and conservation biologists. 3. Spatially dispersed groups of microphones (arrays) enable users to study signal directionality on a small scale or to locate animals and track their movements on a larger scale. 4. Advances in algorithm development can allow users to discriminate among species, sexes, age groups and individuals. 5. With such technology, users can remotely and non-invasively survey populations, describe the soundscape, quantify anthropogenic noise, study species interactions, gain new insights into the social dynamics of sound-producing animals and track the effects of factors such as climate change and habitat fragmentation on phenology and biodiversity. 6. There remain many challenges in the use of acoustic monitoring, including the difficulties in performing signal recognition across taxa. The bioacoustics community should focus on developing a

Array signal processing

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