Multi-Sensor Acoustic Shooter Location via Shockwave and Muzzle Blast Fusion
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Solution Overview
Problem
Conventional systems for determining the origin and direction of supersonic projectiles face challenges in accurately estimating shooter range, especially at long distances, due to weak or unreliable muzzle blast signals, and struggle with disambiguating shock-wave only solutions without sufficient muzzle blast detections.
Innovation Solution
The method involves measuring shockwave and muzzle blast signals at multiple acoustic sensors, using iterative calculations and genetic algorithms to refine shooter range estimates and disambiguate projectile trajectories, even with fewer than four muzzle blast detections, by computing time-difference-of-arrival and arrival angles, and applying genetic algorithms to optimize solutions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional acoustic sensors are used to measure shockwave and muzzle blast signals, then the system can determine shooter direction and trajectory, but the muzzle blast signal becomes weak or unreliable at long distances, making accurate range estimation difficult
Solution Approach 1:
The patent combines shockwave signal measurements with muzzle blast signal measurements into a unified detection system. By merging these two types of acoustic signals and processing them together through a combined algorithm, the system leverages the strengths of both signal types to achieve accurate range estimation even when muzzle blast signals are weak at long distances.
Solution Approach 2:
The patent changes the approach from relying solely on muzzle blast signal amplitude to using time-difference-of-arrival (TDOA) measurements and iterative optimization algorithms. By transforming the problem into a parameter optimization task that considers multiple sensors and signal types, the system achieves accurate range estimation independent of muzzle blast signal strength.
2Measurement precision
If conventional algorithms require at least 4 shockwave and muzzle detections to invert a 4×4 matrix, then mathematical solutions can be obtained, but small errors in TOA determination produce substantial errors in range estimations
Solution Approach 1:
The patent implements an iterative optimization algorithm that uses feedback from multiple sensors and repeated measurements to refine range estimates. The system continuously adjusts its estimates based on residual errors between predicted and actual signal arrivals, reducing the impact of small TOA measurement errors through cumulative refinement rather than single-step calculation.
Solution Approach 2:
The patent uses more than the minimum 4 detections required by conventional matrix inversion methods. By incorporating measurements from multiple sensors and utilizing both shockwave and muzzle blast signals excessively beyond the minimum requirement, the system creates an over-determined system that reduces error through redundancy and optimization.
3Device complexity
If conventional algorithms assume constant bullet speed along the trajectory, then calculations are simplified, but this gives inaccurate range estimates for long-range shots fired from distances greater than approximately 300 meters
Solution Approach 1:
The patent transitions from assuming constant bullet speed to modeling bullet velocity as a dynamic parameter that changes along the trajectory. The optimization algorithm accounts for velocity decay due to air resistance and other factors, allowing the bullet speed to vary iteratively during the range estimation process to achieve accurate long-range shot measurements.
4Reliability
If muzzle blast signals are masked, shadowed or distorted by extraneous noise and reflections, then the signals become difficult to discern from spurious signals, but iterative optimization algorithms can still extract useful information from shockwave-only detections
Solution Approach 1:
The patent extracts and separates shockwave signal information from the total acoustic signal, processing shockwave-only detections independently from muzzle blast signals. By extracting the shockwave component and using it as the primary basis for range estimation, the system achieves reliable shooter location determination even when muzzle blast signals are masked or distorted by environmental factors.
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 enables accurate and reliable estimation of shooter range and disambiguation of projectile trajectories, improving precision and reducing errors, especially for long-range shots and situations with limited muzzle blast signal detection.
Implementation Method 1
measuring parameters associated with the shockwave generated by a projectile
Implementation Method 2
each sensor incorporating three acoustic transducers arranged in a plane. The sensors generate signals in response to the shockwave
Implementation Method 3
measure shockwave and muzzle blast signals at multiple acoustic sensors, using iterative calculations and genetic algorithms to refine shooter range estimates
Data Source
AI summary
Systems and methods for locating the shooter of supersonic projectiles are described. The system uses at least five, preferably seven, spaced acoustic sensors. Sensor signals are detected for shockwaves and muzzle blast, wherein muzzle blast detection can be either incomplete coming from less than 4 sensor channels, or inconclusive due to lack of signal strength. Shooter range can be determined by an iterative computation and/or a genetic algorithm by minimizing a cost function that includes timing information from both shockwave and muzzle signal channels. Disambiguation is significantly improved over shockwave-only measurements.