Abstract: A method of tracking a known object is presented, wherein a sonar image of an object which is distorted by an artifact associated with sonar imaging is compared with an image generated from a model of the object, and at least one of the two images is modified to reduce differences between them.

Abstract: A method of real time three dimensional (3D) sonar imaging is disclosed, where large array of sonar signal detectors images an underwater object and electromagnetic measuring means fixed in a known position with respect to the large array of sonar detectors measure the position of an above water object which has a known position with respect to the underwater object. The position of the sonar detector may be corrected to give a stable image of the underwater object from ping to ping of the sonar imaging system.

Abstract: In a sonar system using a large array multielement sonar detector to detect reflected signals sent out by a sonar ping generator, the sent out sonar ping generator sends out varying frequency sonar signals during each ping, where the frequency is neither monotonically increasing or monotonically decreasing.

Abstract: A sonar system comprising a sonar transmitter, a very large array two dimensional sonar receiver, and a beamformer section transmits a series of sonar pings into an insonified volume of fluid at a rate greater than 5 pings per second, receives sonar signals reflected and scattered from objects in the insonified volume, and beamforms the reflected signals to provide a video presentation and/or to store the beamformed data for later use. The parameters controlling the sonar system are changed so that the beamformer section treats the data from the receiver section with more than one set of parameters. The stream of data is treated either in parallel or in series by different beamforming methods so that at least one beam from the beamformer has more than one value.

Abstract: Technologies for processing imaging data are disclosed, such as sonar images. A computing device obtains a three-dimensional (3D) volumetric view of a space, such as an underwater space. This data includes multiple voxels including a value characterizing a 3D point in the space. The computing device divides this data into slices representing a cross-section of the 3D volumetric view. The computing device clips one or more voxels in these slices based on a weighting function.

Abstract: A sonar system comprising a sonar transmitter, a very large array two dimensional sonar receiver, and a beamformer section transmits a series of sonar pings into an insonified volume of fluid at a rate greater than 5 pings per second, receives sonar signals reflected and scattered from objects in the insonified volume, and beamforms the reflected signals to provide a video presentation and/or to store the beamformed data for later use. The parameters controlling the sonar system are changed so that the beamformer section treats the data from the receiver section with more than one set of parameters. The stream of data is treated either in parallel or in series by different beamforming methods so that at least one beam from the beamformer has more than one value.

Abstract: A sonar system comprising a sonar transmitter, a very large array two dimensional sonar receiver, and a beamformer section transmits a series of sonar pings into an insonified volume of fluid at a rate greater than 5 pings per second, receives sonar signals reflected and scattered from objects in the insonified volume, and beamforms the reflected signals to provide a video presentation and/or to store the beamformed data for later use. The parameters controlling the sonar system are changed between pings to provide enhanced video imaging.

Abstract: A sonar system comprising a sonar transmitter, a very large array two dimensional sonar receiver, and a beamformer section transmits a series of sonar pings into an ensonified volume of fluid at a rate greater than 5 pings per second, receives sonar signals reflected and scattered from objects in the ensonified volume, and beamforms the reflected signals to provide a video presentation and/or to store the beamformed data for later use. The parameters controlling the sonar system are changed so that the beamformer section treats the data from the receiver section with more than one set of parameters per ping and/or neighboring pings. The stream of data is treated either in parallel or in series by different beamforming methods so that at least one beam from the beamformer has more than one value.

Abstract: A method of real time three dimensional (3D) sonar imaging is disclosed, where large array of sonar signal detectors images an underwater object and electromagnetic measuring means fixed in a known position with respect to the large array of sonar detectors measure the position of an above water object which has a known position with respect to the underwater object. The position of the sonar detector may be corrected to give a stable image of the underwater object from ping to ping of the sonar imaging system.

Abstract: A sonar system comprising a sonar transmitter, a very large array two dimensional sonar receiver, and a beamformer section transmits a series of sonar pings into an ensonified volume of fluid at a rate greater than 5 pings per second, receives sonar signals reflected and scattered from objects in the ensonified volume, and beamforms the reflected signals to provide a video presentation and/or to store the beamformed data for later use. The parameters controlling the sonar system are changed so that the beamformer section treats the data from the receiver section with more than one set of parameters. The stream of data is treated either in parallel or in series by different beamforming methods so that at least one beam from the beamformer has more than one value.

Abstract: A method of tracking a known object is presented, wherein a sonar image of an object which is distorted by an artifact associated with sonar imaging is compared with an image generated from a model of the object, and at least one of the two images is modified to reduce differences between them.

Abstract: In a sonar system using a large array multielement sonar detector, the raw phase and intensity data is reduced to less than three bits per channel per slice for each of the detectors in the multielement array before the raw data is transmitted to a beamformer for transforming the data to information about the spatial positions of objects reflecting the sonar signals.

Abstract: Beamformed sonar data is compressed before communicating the data to a storage step or to a further processing step. At lease some of the beams of the compressed beamformed data have values for at least two different ranges.

Abstract: Beamformed sonar data is compressed before communicating the data to a storage step or to a further processing step. At lease some of the beams of the compressed beamformed data have values for at least two different ranges.

Abstract: In a sonar system using a large array multielement sonar detector to detect reflected signals sent out by a sonar ping generator, the sent out sonar ping generator sends out varying frequency sonar signals during each ping, where the frequency is neither monotonically increasing or monotonically decreasing.

Abstract: In a sonar system using a large array multielement sonar detector, the raw phase and intensity data is reduced to less than three bits per channel per slice for each of the detectors in the multielement array before the raw data is transmitted to a beamformer for transforming the data to information about the spatial positions of objects reflecting the sonar signals.

Abstract: An object is measured to record the relative surface coordinates. Then, a portion of the object “the front side” immersed in a fluid is imaged by directing a sonar pulse at the object and recording sonar signals reflected from the object with a sonar imaging array. Then, the recorded relative surface coordinates are iteratively fit to coordinates calculated from the sonar image. Thereafter, the coordinates of the surface of the “backside” of the object that is not observable in the sonar image are known, and a computer generated image of the backside is stitched to sonar image so that the object can be viewed from a plurality of viewpoints separated from the sonar imaging array.

Abstract: An object is measured to record the relative surface coordinates. Then, a portion of the object “the front side” immersed in a fluid is imaged by directing a sonar pulse at the object and recording sonar signals reflected from the object with a sonar imaging array. Then, the recorded relative surface coordinates are iteratively fit to coordinates calculated from the sonar image. Thereafter, the coordinates of the surface of the “backside” of the object that is not observable in the sonar image are known, and a computer generated image of the backside is stitched to sonar image so that the object can be viewed from a plurality of viewpoints separated from the sonar imaging array.

Abstract: An object is measured to record the relative surface coordinates. Then, a portion of the object “the front side” immersed in a fluid is imaged by directing a sonar pulse at the object and recording sonar signals reflected from the object with a sonar imaging array. Then, the recorded relative surface coordinates are iteratively fit to coordinates calculated from the sonar image. Thereafter, the coordinates of the surface of the “backside” of the object that is not observable in the sonar image are known, and a computer generated image of the backside is stitched to sonar image so that the object can be viewed from a plurality of viewpoints separated from the sonar imaging array.

Abstract: Sonar imaging data obtained by sending multiple sonar pings towards an object is reduced by assigning values measured by each sonar ping to bins, where each bin is fixed in World Space, and calculating the opacity of each bin to produce an image of the object. A normal vector associated with each bin is used to calculate the light reflected from a model constructed from the data. The most preferred normal vector is calculated from the vector sum of normals calculated from each ping.