Determining the range to marine mammals in the Northern gulf of mexico via bayesian acoustic signal processing

Abstract

Being able to determine the range or distance to an object from its acoustic signal is a key component in tracking the object. We will apply concepts from the Bayesian processor (Kalman filter) as well as known environmental aspects to LADC-GEMM underwater passive acoustic data: sperm whales, beaked whales and dolphins in the northern Gulf of Mexico. The Bayesian processor has had applications in chemical processing, navigation, ocean acoustics, seismology, and tracking, among others. We will use a modified version of the Kalman filter with data from a single hydrophone to determine the most-probable range of the marine mammal from the hydrophone. We will use such aspects as the geometry of the region, the depth of the hydrophone, the range of possible detection, the structure of the click and other factors to restrict the possible locations of the marine mammal source. From this, we can determine a three-dimensional shell of most probable locations for the marine mammal.

Application of Multiacoustic Data in Feature Extraction of Anemometer

“…After determining the grading, these grades are assigned a score. Five grades are assigned a score by 10 points, namely, excellent grade score interval [8,10], good grade score interval [6,8], qualified grade score interval [4,6], basic qualified grade score interval [2,4], and unqualified grade score interval [0,2]. Table 2 shows the preliminary evaluation results of the experiment.…”

“…In recent years, many mathematicians mainly focus on musical instrument timbre optimization, musical instrument structure improvement, and so on, rarely through acoustic data to study the intelligent instrument recognition system [3]. In China, the research on article feature recognition has a history of decades, involving a lot of content [4]. From the point of view of the evaluation object, it includes conventional cat face recognition, human body recognition, and instrument recognition [5].…”