Millimeter-Wave Radar Target Tracking Using State Machine
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Solution Overview
Problem
Conventional radar systems face challenges in accurately tracking human targets due to issues with distinguishing between human movement and static objects, leading to false positives and inefficient target tracking.
Innovation Solution
A millimeter-wave radar system that performs target detection by investigating movement in every range bin using short-term and long-term movement evaluations, with a state machine to track targets based on their movement states, avoiding false positives by activating tracks only when human movement is confirmed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional radar systems track all detected targets including static objects, then tracking coverage is comprehensive, but false positives increase and tracking efficiency decreases
Solution Approach 1:
The patent applies dynamics by implementing a state machine with multiple states (unsure, moving, static) that transitions based on detected target behavior. The system dynamically adjusts tracking resources by activating tracks only for moving targets while maintaining or killing tracks for static targets, thereby improving reliability without sacrificing productivity
Solution Approach 2:
The patent applies preliminary action by evaluating target movement characteristics before activating full tracking. The state machine performs preliminary assessment in the 'unsure' state, and only activates tracking resources when movement is confirmed, preventing false positives before they consume tracking resources
2Reliability
If motion detection is used to differentiate human targets from static objects, then false positives are reduced, but computational complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the processing into distinct stages: initial detection, state evaluation, and track management. The state machine segments target classification into discrete states (unsure, moving, static) with specific transition criteria, making the complex motion detection process more manageable and efficient
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 tracks human targets by differentiating between human movement and static objects, reducing false positives and improving tracking accuracy with lower computational effort compared to conventional methods.
Implementation Method 1
receiving reflected radar signals with a millimeter-wave radar
Implementation Method 2
transmitting a frequency modulated signal, receiving a reflection of the frequency modulated signal
Implementation Method 3
performing a range discrete Fourier Transform (DFT) based on the reflected radar signals to generate in-phase (I) and quadrature (Q) signals
Data Source
Figure 1~3
Figure 4
Figure 5A~5D
AI summary
In an embodiment, a method includes: receiving reflected radar signals with a millimeter-wave radar; performing a range discrete Fourier Transform (DFT) based on the reflected radar signals to generate in-phase (I) and quadrature (Q) signals for each range bin of a plurality of range bins; for each range bin of the plurality of range bins, determining a respective strength value based on changes of respective I and Q signals over time; performing a peak search across the plurality of range bins based on the respective strength values of each of the plurality of range bins to identify a peak range bin; and associating a target to the identified peak range bin.