Active Sonar Fuzzy Logic Multi-Beam Correlation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional active sonar systems face challenges in accurately detecting and localizing underwater objects in noisy ocean environments, often resulting in false alarms due to the inability to effectively distinguish between target echoes and noise reflections from the ocean surface or bottom, and they discard useful information by processing each receive beam independently.
Innovation Solution
The implementation of a multi-beam based detection system that utilizes crossbeam correlation to enhance weak target signals and reduce false alarms by comparing detection data from adjacent beams, employing fuzzy logic and similarity functions to update detection probability values and fuse target information across overlapping beams.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional single-beam detection is used to process each receive beam independently, then the system is simple to operate and has low computational complexity, but it discards useful information from adjacent beams and produces false alarms due to inability to distinguish target echoes from noise reflections
Solution Approach 1:
The patent combines detection information from multiple adjacent receive beams by computing a similarity function that compares range cell data across beams. This merging of information from multiple sources allows the system to distinguish true target echoes from noise reflections, improving detection accuracy while using fuzzy logic to manage the computational complexity of the integration process.
Solution Approach 2:
The patent introduces a similarity function as an intermediary mechanism that compares range cell data from adjacent beams. This intermediary computation enables the system to identify correlated targets across multiple beams while filtering out uncorrelated noise, thereby improving measurement precision without requiring direct complex multi-beam processing.
2Productivity
If detection threshold is lowered to increase probability of detecting real targets, then detection rate improves, but false alarm rate increases due to noisy ocean environment
Solution Approach 1:
The patent employs fuzzy logic detection that provides feedback by iteratively updating detection probability values based on similarity comparisons across multiple beams. This feedback mechanism allows the system to adjust detection decisions dynamically, maintaining high detection rates while suppressing false alarms through continuous refinement of detection confidence levels.
Solution Approach 2:
The patent changes the detection parameter from a simple threshold-based approach to a probability-based approach using fuzzy logic. By transforming the detection criterion into a continuous probability value that incorporates information from multiple beams, the system can differentiate between weak true targets and noise reflections, improving both detection rate and reliability simultaneously.
3Reliability
If sophisticated detection processing algorithms are applied to reduce false alarms, then false alarm rate decreases, but detection probability of real targets also decreases
Solution Approach 1:
The patent merges detection information from multiple adjacent beams using a similarity function, which combines evidence from multiple sources to support true target detections while suppressing false alarms. This merging approach maintains high detection probability for real targets because true targets appear consistently across multiple beams, whereas false alarms remain isolated to single beams.
4Measurement precision
If multi-beam based detection with crossbeam correlation is implemented to enhance weak target signals and reduce false alarms, then detection accuracy and robustness improve, but computational complexity and processing time increase
Solution Approach 1:
The patent implements partial multi-beam processing by computing similarity functions only for adjacent beams that are most likely to contain relevant target information, rather than processing all possible beam combinations. This partial action approach maintains high detection accuracy for weak targets while reducing the computational burden and processing time associated with exhaustive multi-beam analysis.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach leads to more accurate and robust detection results with improved detection rates and reduced false alarm rates compared to single-beam based systems, enhancing the ability to detect and localize underwater objects in noisy environments.
Implementation Method 1
Some of the acoustic energy reflects from objects in or on the water back toward the active sonar system. These reflections, referred to as 'echoes,' are received by acoustic sensors at the active sonar system.
Implementation Method 2
a conventional active sonar system transmits a burst of acoustic energy, called a 'ping,' which travels at the speed of sound through the water
Implementation Method 3
a conventional active sonar system transmits a burst of acoustic energy, called a 'ping,' which travels at the speed of sound through the water
Data Source
AI summary
A computer-implemented method of sonar processing includes identifying, with a processor, a detection having a detection probability value, the detection in a selected beam, wherein the detection is associated with a detection range cell having detection range cell data. The method also includes comparing, with the processor, the detection range cell data with range cell data from a corresponding range cell from at least one overlapping beam overlapping the selected beam. The method also includes updating, with the processor, the detection probability value based upon the comparing. A sonar system uses the above-described method. A computer readable storage medium has instructions thereon to achieve the above-described method.