Single-Antenna Radar Object Detection Using Clustering and Association
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional radar systems require multiple antennas and complex RF front-end circuits to determine object angles and velocities, leading to increased cost and complexity, especially when used in vehicle radar systems for estimating object trajectories.
Innovation Solution
An object detection system that includes a transmitter, a receiver, and a processing circuit, which transmits detection signals along a main beam direction, receives reflection signals, calculates received powers, distances, and velocities, performs clustering and association processes to track main targets, and determines whether an early warning event will occur based on power and distance trends.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple antennas are used to determine azimuth and elevation angles, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent extracts only the necessary function (distance and velocity measurement) from the complete radar system, eliminating the angle determination function. This allows the system to use a single antenna instead of multiple antennas, reducing device complexity while maintaining essential object detection capabilities through clustering-based target identification
Solution Approach 2:
The patent replaces expensive, complex multiple-antenna hardware with a simpler single-antenna system combined with signal processing algorithms. The clustering process acts as a computational substitute for hardware complexity, achieving target separation and tracking through software rather than additional physical components
2Measurement precision
If more RF front-end circuits are added for multiple antennas, then measurement precision is improved, but manufacturing cost increases
Solution Approach 1:
The patent removes the need for multiple RF front-end circuits by extracting only the essential distance and velocity measurement functions. The single-antenna configuration with clustering-based signal processing achieves adequate target detection precision without requiring multiple expensive RF chains
Solution Approach 2:
The patent replaces the mechanical/hardware approach of using multiple antennas and RF circuits with a signal processing approach. The clustering algorithm processes signals computationally to achieve target separation and tracking, substituting complex hardware with software-based solutions that reduce manufacturing costs
3Measurement precision
If additional cameras are added for trajectory estimation, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent makes the radar system multi-functional by enabling it to perform both object detection and trajectory estimation using the same single-antenna hardware. The association process tracks targets across multiple time frames, allowing the system to derive trajectory information without requiring separate camera systems
Solution Approach 2:
The radar system serves itself by using its own reflected signals to extract multiple parameters including distance, velocity, and trajectory information. The clustering and association processes enable the system to self-determine object tracks without external sensors, reducing overall system complexity
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 effectively estimates object trajectories without additional hardware modifications, reduces the need for accurate angle determination, and minimizes the number of RF front-end circuits and analog-to-digital converters, resulting in lower costs and complexity compared to conventional radar systems.
Implementation Method 1
Signals transmitted by the radar system hit an object and are reflected to the receiver
Data Source
AI summary
An object detection system and an object detection method are provided. The object detection system includes a transmitter, a receiver, and a processing circuit. The processing circuit is configured to: control the transmitter to transmit by a predetermined field pattern multiple detection signals in different time frames along a main beam direction; control the receiver to receive multiple reflection signals; correspondingly calculate multiple received powers, distances and velocities; perform a clustering process on the distances and the velocities to find the received powers, the distances and the velocities corresponding to a main target; perform an association process to track the distances and the received powers of the main target in the different time frames; and calculate a power and a distance trend of the main target, and determine whether an early alarm event is to occur according to a relationship between the power and the distance trend.