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Autonomous Underwater Vehicles (AUVs) are being used successfully in underwater Mine Counter Measures(MCM) operations by Navies around the world. This approach reduces the risk to life of ship’s crew by autonomously detecting and neutralizing mines while mothership is at a safe standoff distance. For MCM operations, AUVs employ high frequency acoustic Side Imaging Sonars like Side Scan Sonar(SSS) or Synthetic Aperture Sonar (SAS) to detect, classify, and localize Mine Like Objects(MLOs) on the ocean floor. Our proposed Post Processing requirements for detection, localization and classification of MLOs require better along track and across track resolution of the Side Imaging Sonar. The along track resolution requirement can be better met with SAS imagery as compared with SSS imagery. The proposed MCM methodology consists of : a). AUV Path Planning: The AUV path planning is done when the AUV is at the mother platform(ship). The current location of the AUV is updated (through GPS) . Once the AUV dips into water, the inbuilt Inertial Navigation System(INS) updates the current location of the AUV. Depending upon the mission requirements , the AUV goes to a designated area and starts scanning the area. The AUV’s path and scanning speed depends on the Synthetic Aperture Sonar’s swath coverage, array length and the presence/absence of a gap filler sonar with it. AUV path planning along with AUV’s restricted tolerance in pitch, roll and yaw (very accurate INS) is very critical for better SAS image formation. b). Synthetic Aperture Sonar(SAS) scanning to obtain sonar image of the ocean floor: The SAS image of the designated area is generated. The sonar image so obtained is divided into small sub-images (of say 20m x 20m). c). Online Automatic Target Recognition(ATR) using 1).Content Based Image Retrieval(CBIR), and 2). Image Edge Detector 1).Content Based Image Retrieval (CBIR): CBIR is based on i). feature extraction of each sub-image (query image) and ii). conducting a similarity measure for matching an image from the database closest to the query image in terms of feature vector. An essential requirement of CBIR is the availability of a very extensive feature-rich database of SAS images. This is required in the training/learning phase(done offline before AUV mission) of CBIR. We have taken SAS sonar images of Mine Like Objects (MLOs) available freely online. Due to limited availability of such sonar images and to make an extensive feature-rich database, we have also used some optical images of similar objects in the database. We have considered a weighted combination of features like texture, shape, mathematical moments, spatial relationships, etc. to make the feature vector. The output of CBIR processing is the sonar image(say image no. n) from the database closest to the query image in terms of the feature vector. We have the prior information about the image no. n (which was processed offline during the training phase). If the image no. n belongs to the Mine Like Objects (MLOs) cluster in the database, we consider this query image as a valid detection and do further processing. The above information is then confirmed with a magnetometer sensor output of the AUV. If both the data indicate positive presence of mine, a decision about presence of mine is taken online by the AUV. (2). Image Edge Detector: The sonar query image (validated as a mine) is then processed by Canny Edge Detector. This results in a low resolution image (in kBs) compared to the high resolution query image (in MBs). d). Update mother platform in real time: The low resolution edge-detected image (in kBs) is then transmitted through underwater acoustic communication(low bandwidth channel) to the mother platform along with location of the mine (from INS data). In case of unavailability of the above channel, the AUV periodically surfaces and transmits high resolution sub-image (in MBs) to mother platform using high bandwidth Line of Sight (LoS) communication. If this channel is also not available, the Satellite Communication (low bandwidth channel) is used to transmit the low resolution edge-detected image (in kBs) and location of the suspected mine to the mother platform for further action.
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