Atomic Norm Signal Denoising for Low-Power Target Detection
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Solution Overview
Problem
Existing radar, LIDAR, and sonar systems face limitations in range and angular resolution, are costly, and require high transmitter output power, with conventional methods suffering from noise interference and inefficient signal processing.
Innovation Solution
Implementing a sensor system with an optimization procedure using projected gradient descent and atomic norm minimization to denoise echo signals, allowing for improved target detection and estimation of distance, angle of arrival, and velocity by reducing noise and enhancing signal processing efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Length of stationary object
If the transmitter output power is increased to improve target detection range, then the detection range is extended, but the power consumption and cost increase
Solution Approach 1:
The patent applies preliminary action by performing denoising operations on received signals before range estimation. The system receives multiple signals, denoises them using optimization procedures, and then performs range estimation on the denoised signals. This preliminary processing improves detection sensitivity without requiring increased transmitter power.
2Measurement precision
If conventional radar systems are used to achieve accurate target detection, then detection accuracy is maintained, but the system cost is high
Solution Approach 1:
The patent replaces conventional mechanical signal processing methods with optimization-based denoising procedures. Instead of using traditional filtering or noise reduction techniques, the system formulates denoising as an optimization problem that minimizes a cost function combining signal fidelity and denoising performance. This substitution achieves superior detection accuracy without requiring expensive conventional radar infrastructure.
3Measurement precision
If signal processing complexity is increased to improve denoising performance, then noise reduction is enhanced, but computational requirements increase
Solution Approach 1:
The patent applies parameter changes by formulating the denoising problem in terms of optimizing specific parameters within a cost function. The system adjusts regularization parameters and optimization constraints to balance denoising performance with computational efficiency. This allows the system to achieve high signal-to-noise ratio improvement while controlling computational complexity through parameter selection.
Data Source
AI summary
Disclosed herein are systems and methods for estimating target ranges, angles of arrival, and speed using optimization procedures. Target ranges are estimated by performing an optimization procedure to obtain a denoised signal, performing a correlation of a transmitted waveform and the denoised signal, and using a result of the correlation to determine an estimate of a distance between the sensor and at least one target. Target angles of arrival are estimated by determining ranges at which targets are located, and, for each range, constructing an array signal from samples of received echo signals, and using the array signal, performing another optimization procedure to estimate a respective angle of arrival for each target of the at least one target. Doppler shifts may also be estimated using another optimization procedure. Certain of the optimization procedures use atomic norm techniques.