Gunshot Detection Signal Processing Using Goertzel Algorithm and Gradient Boosting
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Solution Overview
Problem
Current gunshot detection systems fail to accurately distinguish gunshot sounds from other noises and determine their location in a timely and reliable manner, which is crucial for effective response to active shooter incidents.
Innovation Solution
A system utilizing a Goertzel algorithm-based digital signal filter to process acoustic signals, identifying key frequencies associated with gunshots, and employing gradient boosting decision trees to predict gunshot occurrences, coupled with a debouncer to suppress duplicate alerts, is implemented. This system includes sensors that convert analog sound signals into digital, apply the Goertzel algorithm to specific frequencies, and transmit data to a cloud network for processing and notification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional gunshot detection systems are used, then gunshot detection is provided, but accuracy in distinguishing gunshot sounds from other noises is insufficient and false alarms occur
Solution Approach 1:
The patent segments the acoustic signal analysis into multiple discrete frequency bands (e.g., 500-1000 Hz, 1000-2000 Hz, etc.) and applies Goertzel algorithm filters to each band independently. This segmentation allows the system to identify specific frequency patterns characteristic of gunshots while filtering out noise in other frequency ranges, thereby improving both reliability and measurement precision.
Solution Approach 2:
The patent transforms the acoustic signal from time-domain to frequency-domain representation by analyzing magnitude and phase parameters across multiple discrete frequencies. By monitoring changes in these parameters over time and comparing them against trained patterns, the system achieves more precise distinction between gunshot sounds and other noises, resolving the contradiction between reliability and measurement precision.
2Measurement precision
If complex signal processing is applied to improve gunshot identification accuracy, then detection precision improves, but processing time and system complexity increase
Solution Approach 1:
The patent extracts only the relevant frequency components from the full acoustic spectrum by applying Goertzel algorithm filters to specific discrete frequency bands. This extraction approach focuses computational resources on the most diagnostically useful frequency ranges for gunshot detection, maintaining high measurement precision while reducing overall processing time compared to analyzing the entire frequency spectrum.
Solution Approach 2:
The system performs preliminary filtering and feature extraction using the Goertzel algorithm before applying the more computationally intensive gradient boosting classification. By pre-processing the signal to identify and isolate characteristic frequency patterns, the system reduces the complexity and time of subsequent analysis, effectively balancing precision with processing speed.
3Measurement precision
If multiple frequency analysis is performed to improve location accuracy, then detection precision improves, but device complexity increases
Solution Approach 1:
The Goertzel algorithm-based filter bank serves multiple functions simultaneously: it performs frequency analysis for gunshot identification, provides magnitude and phase information for location determination, and enables real-time processing. This multi-functionality allows the system to achieve high measurement precision for both identification and location without proportionally increasing device complexity, as a single computational framework handles multiple analytical tasks.
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
The system accurately identifies gunshot sounds and their location, reducing false alarms and providing timely information to occupants and responders, thereby enhancing response efficiency and safety.
Implementation Method 1
converting the acoustic signals to a digital signal and then employing a Goertzel algorithm based digital signal filter on the digital signal to produce Goertzel magnitudes at the plurality of discrete frequencies
Implementation Method 2
receiving acoustic signals at a microphone indicative of a magnitude of the acoustic signal at a plurality of discrete frequencies
Implementation Method 3
the method predicts if the Goertzel magnitudes at the plurality of discrete frequencies are indicative of a gunshot sound via gradient boosting
Data Source
AI summary
A system and method for detecting the occurrence of a gunshot are provided. The method may include receiving acoustic signals at a microphone indicative of a magnitude of the acoustic signal at a plurality of discrete frequencies, converting the acoustic signals to a digital signal and then employing a Goertzel algorithm based digital signal filter on the digital signal to produce Goertzel magnitudes at the plurality of discrete frequencies. The method subsequently determines if a maximum value of the digital signal is higher than a predefined threshold value. If the threshold value is exceeded, the method predicts if the Goertzel magnitudes at the plurality of discrete frequencies are indicative of a gunshot sound via gradient boosting; and, transmits a signal indicative of a gunshot occurrence after predicting if a possible gunshot event has occurred. A debouncer may also be utilized to suppress duplicative signals.