scispace - formally typeset
Search or ask a question
Topic

Sonar

About: Sonar is a research topic. Over the lifetime, 12892 publications have been published within this topic receiving 128029 citations. The topic is also known as: Sound Navigation And Ranging & Sound Navigation and Ranging.


Papers
More filters
Proceedings ArticleDOI
25 Mar 1985
TL;DR: The use of multiple wide-angle sonar range measurements to map the surroundings of an autonomous mobile robot deals effectively with clutter, and can be used for motion planning and for extended landmark recognition.
Abstract: We describe the use of multiple wide-angle sonar range measurements to map the surroundings of an autonomous mobile robot. A sonar range reading provides information concerning empty and occupied volumes in a cone (subtending 30 degrees in our case) in front of the sensor. The reading is modelled as probability profiles projected onto a rasterized map, where somewhere occupied and everywhere empty areas are represented. Range measurements from multiple points of view (taken from multiple sensors on the robot, and from the same sensors after robot moves) are systematically integrated in the map. Overlapping empty volumes re-inforce each other, and serve to condense the range of occupied volumes. The map definition improves as more readings are added. The final map shows regions probably occupied, probably unoccupied, and unknown areas. The method deals effectively with clutter, and can be used for motion planning and for extended landmark recognition. This system has been tested on the Neptune mobile robot at CMU.

1,911 citations

Journal ArticleDOI
TL;DR: A new theoretical result is presented: the joint probabilistic data association (JPDA) algorithm, in which joint posterior association probabilities are computed for multiple targets (or multiple discrete interfering sources) in Poisson clutter.
Abstract: The problem of associating data with targets in a cluttered multi-target environment is discussed and applied to passive sonar tracking. The probabilistic data association (PDA) method, which is based on computing the posterior probability of each candidate measurement found in a validation gate, assumes that only one real target is present and all other measurements are Poisson-distributed clutter. In this paper, a new theoretical result is presented: the joint probabilistic data association (JPDA) algorithm, in which joint posterior association probabilities are computed for multiple targets (or multiple discrete interfering sources) in Poisson clutter. The algorithm is applied to a passive sonar tracking problem with multiple sensors and targets, in which a target is not fully observable from a single sensor. Targets are modeled with four geographic states, two or more acoustic states, and realistic (i.e., low) probabilities of detection at each sample time. A simulation result is presented for two heavily interfering targets illustrating the dramatic tracking improvements obtained by estimating the targets' states using joint association probabilities.

1,421 citations

Journal ArticleDOI
01 Jun 1991
TL;DR: An algorithm for, model-based localization that relies on the concept of a geometric beacon, a naturally occurring environment feature that can be reliably observed in successive sensor measurements and can be accurately described in terms of a concise geometric parameterization, is developed.
Abstract: The application of the extended Kaman filter to the problem of mobile robot navigation in a known environment is presented. An algorithm for, model-based localization that relies on the concept of a geometric beacon, a naturally occurring environment feature that can be reliably observed in successive sensor measurements and can be accurately described in terms of a concise geometric parameterization, is developed. The algorithm is based on an extended Kalman filter that utilizes matches between observed geometric beacons and an a priori map of beacon locations. Two implementations of this navigation algorithm, both of which use sonar, are described. The first implementation uses a simple vehicle with point kinematics equipped with a single rotating sonar. The second implementation uses a 'Robuter' mobile robot and six static sonar transducers to provide localization information while the vehicle moves at typical speeds of 30 cm/s. >

1,394 citations

Journal ArticleDOI
01 Jun 1987
TL;DR: In this article, a sonar-based mapping and navigation system for an autonomous mobile robot operating in unknown and unstructured environments is described, where range measurements from multiple points of view are integrated into a sensor level sonar map, using a robust method that combines the sensor information in such a way as to cope with uncertainties and errors in the data.
Abstract: A sonar-based mapping and navigation system developed for an autonomous mobile robot operating in unknown and unstructured environments is described. The system uses sonar range data to build a multileveled description of the robot's surroundings. Sonar readings are interpreted using probability profiles to determine empty and occupied areas. Range measurements from multiple points of view are integrated into a sensor-level sonar map, using a robust method that combines the sensor information in such a way as to cope with uncertainties and errors in the data. The resulting two-dimensional maps are used for path planning and navigation. From these sonar maps, multiple representations are developed for various kinds of problem-solving activities. Several dimensions of representation are defined: the abstraction axis, the geographical axis, and the resolution axis. The sonar mapping procedures have been implemented as part of an autonomous mobile robot navigation system called Dolphin. The major modules of this system are described and related to the various mapping representations used. Results from actual runs are presented, and further research is mentioned. The system is also situated within the wider context of developing an advanced software architecture for autonomous mobile robots.

1,313 citations

Journal ArticleDOI
TL;DR: This paper shows that the configuration with spatially orthogonal signal transmission is equivalent to additional virtual sensors which extend the array aperture with virtual spatial tapering and provides higher performance in target detection, angular estimation accuracy, and angular resolution.
Abstract: In this paper, we propose a new space-time coding configuration for target detection and localization by radar or sonar systems. In common active array systems, the transmitted signal is usually coherent between the different elements of the array. This configuration does not allow array processing in the transmit mode. However, space-time coding of the transmitted signals allows to digitally steer the beam pattern in the transmit in addition to the received signal. The ability to steer the transmitted beam pattern, helps to avoid beam shape loss. We show that the configuration with spatially orthogonal signal transmission is equivalent to additional virtual sensors which extend the array aperture with virtual spatial tapering. These virtual sensors can be used to form narrower beams with lower sidelobes and, therefore, provide higher performance in target detection, angular estimation accuracy, and angular resolution. The generalized likelihood ratio test for target detection and the maximum likelihood and Cramer-Rao bound for target direction estimation are derived for an arbitrary signal coherence matrix. It is shown that the optimal performance is achieved for orthogonal transmitted signals. Target detection and localization performances are evaluated and studied theoretically and via simulations

990 citations


Network Information
Related Topics (5)
Signal processing
73.4K papers, 983.5K citations
77% related
Noise
110.4K papers, 1.3M citations
75% related
Signal
674.2K papers, 4.5M citations
74% related
Filter (signal processing)
81.4K papers, 1M citations
74% related
Kalman filter
48.3K papers, 936.7K citations
72% related
Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023294
2022694
2021289
2020424
2019559
2018537