Shooting Range Estimation via Acoustic Signal Segmentation
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Solution Overview
Problem
Existing methods for predicting shooting range and bullet caliber using acoustic signals from firearms suffer from high prediction errors due to assumptions based on specific conditions, environmental factors like turbulence, and the need for multiple microphones, which increases processing load and costs, and are unreliable in noisy environments.
Innovation Solution
A method using a single microphone to detect shock waves and muzzle blasts, estimating arrival time differences, and applying novel equations to predict miss distance and bullet caliber without parameter adjustments, leveraging the Whitham shock wave model and Fast Fourier Transform for signal processing, allowing for accurate range estimation independent of serial geometry and microphone number.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple microphone series are used for range prediction, then measurement precision may improve, but device complexity and processing costs increase
Solution Approach 1:
The patent segments the acoustic signal analysis into distinct components: shock wave detection and muzzle blast detection. By processing these segmented signals separately through their respective algorithms (Whitham model for shock wave, Friedlander model for muzzle blast), the system achieves accurate range prediction without requiring multiple microphone series, thus reducing device complexity while maintaining measurement precision.
Solution Approach 2:
The patent introduces an intermediary parameter - the time difference between shock wave arrival and muzzle blast arrival - which serves as a mediator to calculate range. This intermediary approach allows accurate range prediction using a single microphone by leveraging the temporal relationship between two acoustic events, avoiding the need for complex multi-microphone spatial arrangements.
2Measurement precision
If ballistic assumptions are made for miss distance prediction, then prediction can be made, but prediction errors increase due to atmospheric effects and bullet type variations
Solution Approach 1:
The patent changes the fundamental parameter used for miss distance prediction from ballistic parameters (bullet caliber, velocity, trajectory) to acoustic signal parameters (time difference between shock wave and muzzle blast, signal characteristics). This parameter change makes the prediction method adaptable to all bullet types and atmospheric conditions without requiring specific ballistic assumptions, thereby improving both accuracy and versatility.
Solution Approach 2:
The patent replaces the mechanical/ballistic system (tracking bullet physics, atmospheric drag, turbulence effects) with an acoustic signal processing system. By substituting mechanical prediction methods with acoustic signal analysis using established models (Whitham, Friedlander), the system achieves universal applicability across different bullet types while maintaining high prediction accuracy.
3Measurement precision
If shock wave and muzzle blast detection is used for range prediction, then range can be estimated, but the method fails in noisy environments where zero transition may not occur
Solution Approach 1:
The patent employs feedback mechanisms in the signal processing algorithms. The Whitham shock wave model and Friedlander muzzle blast model use iterative fitting approaches that continuously adjust parameters based on the detected signal characteristics. This feedback loop allows the system to distinguish genuine acoustic events from background noise, maintaining reliability in noisy environments while preserving range estimation accuracy.
Solution Approach 2:
The patent applies preliminary signal processing and model fitting before making the critical zero transition detection. By pre-processing the acoustic signal through established physical models (Whitham for shock wave, Friedlander for muzzle blast) and fitting procedures, the system prepares the data in advance, making the subsequent range calculation more robust against noise and preventing false detections in challenging acoustic environments.
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 method achieves high accuracy in predicting shooting range and bullet caliber with reduced errors and costs, eliminating the need for network installations and synchronization, and operates effectively in various scenarios, including noisy environments.
Implementation Method 1
detection of acoustic signals from shooting of firearms with supersonic bullets by at least one microphone
Implementation Method 2
Whitham shock wave model
Implementation Method 3
estimation of arrival time difference between detected shock wave and muzzle blast
Data Source
AI summary
A method providing an estimation of a shooting range with high accuracy by a miss distance estimation and a weapon caliber classification following detection of shooting of firearms with supersonic bullets, and by using novel equations constructed from field shooting data for each caliber in order to ensure a security of a patrol station, a border, troops, a society, a vehicle and a convoy is provided.