FMCW MIMO Radar Multi-Target Detection via Sequential Interference Cancellation
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Solution Overview
Problem
Conventional MUSIC algorithms used for estimating distances, azimuths, and velocities of multiple targets in radar systems have high computational complexity and are heavily affected by noise, making them unsuitable for autonomous driving applications.
Innovation Solution
A method and apparatus using a FMCW MIMO radar that generates and cancels interference using orthogonal projection-based techniques, reducing computational complexity and improving estimation accuracy by sequentially estimating parameters of multiple targets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the conventional MUSIC algorithm is used to estimate target parameters, then the estimation accuracy is improved, but the computational complexity increases and noise sensitivity worsens
Solution Approach 1:
The patent segments the target detection process into sequential stages: first detecting and estimating parameters of the closest target, then canceling its interference, and finally detecting the next target. This segmentation reduces the computational complexity of each stage while maintaining overall estimation accuracy, directly resolving the contradiction between precision and complexity.
Solution Approach 2:
The patent performs preliminary detection and parameter estimation of the closest target before processing other targets. By first identifying the dominant target and canceling its interference, the system simplifies subsequent detection tasks, reducing overall computational complexity while improving noise robustness through sequential processing.
2Measurement precision
If the conventional MUSIC algorithm is used to estimate target parameters, then the estimation accuracy is improved, but the noise interference increases
Solution Approach 1:
The patent converts the harmful interference from dominant targets into a beneficial processing sequence. By first detecting and canceling the interference from the closest target, the system transforms the noise problem into a structured solution where each target is processed in order of distance, reducing the impact of noise on overall estimation accuracy.
3Quantity of substance
If multiple targets are detected simultaneously using conventional methods, then the detection coverage is improved, but the computational complexity and error rate increase
Solution Approach 1:
The patent applies segmentation by dividing the multi-target detection into sequential single-target detection stages. Each target is detected, its parameters estimated, and its interference canceled before moving to the next target. This approach maintains detection coverage for multiple targets while improving parameter estimation accuracy by reducing the complexity and error accumulation associated with simultaneous processing.
Data Source
AI summary
An operation method performed by an apparatus for detecting multiple targets may comprise transmitting first signals using Mt transmit antennas included in the apparatus; receiving the first signals reflected by the multiple targets through Mr receive antennas included in the apparatus; generating a first function for estimating a velocity and an azimuth of each of the multiple targets using the first signals and the reflected first signals; estimating a velocity and an azimuth that maximize a result of the first function as a velocity and an azimuth of a first target closest to the apparatus among the multiple targets; generating a second function by cancelling interference caused by the first target from the first function; and estimating a velocity and an azimuth that maximize a result of the second function as a velocity and an azimuth of a second target among the multiple targets.