Acoustic Object Detector Reducing Power Consumption via Spike Generation
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Solution Overview
Problem
Conventional acoustic sensors face challenges in reducing power consumption while maintaining effective signal detection, often leading to missed signals or unnecessary power usage due to inefficient front-end circuit operation.
Innovation Solution
The implementation of a nonlinear acoustic object detector that uses bandpass filters, spike generating circuits, and decision circuits to adaptively process signals, reducing power consumption by adjusting the performance of the front-end circuit based on detected acoustic activity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If duty cycling method is used to periodically shut off front-end circuit, then power consumption is reduced, but important signals may be missed
Solution Approach 1:
The patent implements a wake-up circuit that continuously monitors acoustic energy levels before the front-end circuit is activated. This preliminary detection allows the system to determine whether activation is necessary, preventing premature shutdowns that would miss important signals while still reducing power consumption during silent periods.
Solution Approach 2:
The patent introduces an energy detection circuit as an intermediary between the acoustic environment and the front-end circuit. This intermediary continuously monitors acoustic energy levels and controls the activation state of the front-end circuit, enabling intelligent power management without compromising signal detection reliability.
2Use of energy by moving object
If wake-up circuit is used to detect energy distribution and control front-end circuit activation, then power consumption is reduced, but front-end circuit may wake up even when desired sound signal is not present
Solution Approach 1:
The patent implements multiple energy detection thresholds corresponding to different signal types and importance levels. By using localized thresholds for different acoustic scenarios rather than a single global threshold, the system can distinguish between irrelevant noise and important signals, reducing false wake-ups while maintaining detection accuracy.
Solution Approach 2:
The patent employs dynamic threshold adjustment where detection thresholds are adapted based on ambient noise levels and historical signal patterns. This dynamic adaptation allows the wake-up circuit to distinguish between background noise and meaningful signals, reducing false activations while maintaining sensitivity to important acoustic events.
3Use of energy by moving object
If DSP is used to identify frequency characteristics and scale power consumption, then power efficiency is improved, but hardware complexity and latency increase
Solution Approach 1:
The patent extracts only the essential energy detection function from the full DSP processing chain and implements it as a dedicated wake-up circuit. By separating this simple energy monitoring task from complex frequency analysis, the system achieves power management capability without the hardware complexity and latency of full DSP processing.
Solution Approach 2:
The patent replaces complex digital signal processing operations with simpler analog energy detection circuitry for the wake-up function. This substitution uses basic analog components to perform energy level detection, avoiding the need for complex DSP hardware while achieving effective power management.
Data Source
AI summary
An acoustic object detector for detecting presence of an acoustic signal is provided. The acoustic object detector includes a number of bandpass filters. Each bandpass filter is configured to convert an input signal into an analog signal within a frequency band. The acoustic object detector also includes a number of spike generating circuits each coupled to the respective bandpass filter. Each spike generating circuit is configured to generate a series of spike signals based upon an adaptive threshold for the analog signal. The acoustic object detection further includes a decision circuit configured to generate a digital signal at a time-frequency point from the series of spike signals.