A novel estimation algorithm is introduced to handle the popular undersea problem called torpedo tracking with angle-only measurements with a better approach compared to the existing filters. The new algorithm produce...A novel estimation algorithm is introduced to handle the popular undersea problem called torpedo tracking with angle-only measurements with a better approach compared to the existing filters. The new algorithm produces a better estimate from the outputs produced by the traditional nonlinear approaches with the assistance of simple noise minimizers like maximum likelihood filter or any other algorithm which belongs to their family. The introduced method is extended to the higher version in two ways. The first approach extracts a better estimate and covariance by enhancing the count of the intermediate filters, while the second approach accepts more inputs so as to attain improved performance without enhancement of the intermediate filter count. The ideal choice of the placement of towed array sensors to improve the performance of the proposed method further is suggested as the one where the line of sight and the towed array are perpendicular. The results could get even better by moving the ownship in the direction of reducing range. All the results are verified in the MATLAB environment.展开更多
Understanding the movement of animals is fundamental to population and community ecology. Historically, it has been difficult to quantify movement patterns of most fishes, but technological advances in acoustic teleme...Understanding the movement of animals is fundamental to population and community ecology. Historically, it has been difficult to quantify movement patterns of most fishes, but technological advances in acoustic telemetry have increased our abilities to monitor their movement. In this study, we combined small-scale active acoustic tracking with large-scale passive acoustic monitoring to develop an empirical movement model for sixgill sharks in Puget Sound, WA, USA. We began by testing whether a correlated random walk model described the daily movement of sixgills; however, the model failed to capture home-ranging behavior. We added this behavior and used the resultant model (a biased random walk model) to determine whether daily movement patterns are able to explain large-scale seasonal movement. The daily model did not explain the larger-scale pat- terns of movement observed in the passive monitoring data. In order to create the large-scale patterns, sixgills must have per- formed behaviors (large, fast directed movements) that were unobserved during small-scale active tracking. In addition, seasonal shifts in location were not captured by the dally model. We added these 'unobserved' behaviors to the model and were able to capture large-scale seasonal movement of sixgill sharks over 150 days. The development of empirical models of movement al- lows researchers to develop hypotheses and test mechanisms responsible for a species movement behavior and spatial distribution. This knowledge will increase our ability to successfully manage species of concern [Current Zoology 58 (1): 103-115, 2012].展开更多
文摘A novel estimation algorithm is introduced to handle the popular undersea problem called torpedo tracking with angle-only measurements with a better approach compared to the existing filters. The new algorithm produces a better estimate from the outputs produced by the traditional nonlinear approaches with the assistance of simple noise minimizers like maximum likelihood filter or any other algorithm which belongs to their family. The introduced method is extended to the higher version in two ways. The first approach extracts a better estimate and covariance by enhancing the count of the intermediate filters, while the second approach accepts more inputs so as to attain improved performance without enhancement of the intermediate filter count. The ideal choice of the placement of towed array sensors to improve the performance of the proposed method further is suggested as the one where the line of sight and the towed array are perpendicular. The results could get even better by moving the ownship in the direction of reducing range. All the results are verified in the MATLAB environment.
文摘Understanding the movement of animals is fundamental to population and community ecology. Historically, it has been difficult to quantify movement patterns of most fishes, but technological advances in acoustic telemetry have increased our abilities to monitor their movement. In this study, we combined small-scale active acoustic tracking with large-scale passive acoustic monitoring to develop an empirical movement model for sixgill sharks in Puget Sound, WA, USA. We began by testing whether a correlated random walk model described the daily movement of sixgills; however, the model failed to capture home-ranging behavior. We added this behavior and used the resultant model (a biased random walk model) to determine whether daily movement patterns are able to explain large-scale seasonal movement. The daily model did not explain the larger-scale pat- terns of movement observed in the passive monitoring data. In order to create the large-scale patterns, sixgills must have per- formed behaviors (large, fast directed movements) that were unobserved during small-scale active tracking. In addition, seasonal shifts in location were not captured by the dally model. We added these 'unobserved' behaviors to the model and were able to capture large-scale seasonal movement of sixgill sharks over 150 days. The development of empirical models of movement al- lows researchers to develop hypotheses and test mechanisms responsible for a species movement behavior and spatial distribution. This knowledge will increase our ability to successfully manage species of concern [Current Zoology 58 (1): 103-115, 2012].