User Quote:
“DFR C4001 works okay for presence, but it seems it can’t output multiple target coordinates simultaneously?”
(Source: Arduino Forum)
Introduction: The Challenge of Multi-Person Tracking
In office management, smart homes, security surveillance, and elderly monitoring, real-time tracking of multiple targets is a core requirement. However, entry-level mmWave radars are often reported to only detect a single target or presence/motion state, making it difficult to obtain coordinates for multiple people.
According to the National Institute of Standards and Technology (NIST), low-resolution radars significantly increase detection errors when the number of targets exceeds 2–3. This explains why many developers encounter challenges in real-world applications.
For more details on radar technologies, visit our mmWave Radar Technology Page.
Single-Target vs Multi-Target Tracking: Technical Principles
Doppler Spectrum Separation
MmWave radars measure target distance via phase changes in the returned signal and velocity via Doppler shift. While single-target signals are clear, multiple targets generate overlapping frequency spectra, complicating detection.
Reference: IEEE Transactions on Microwave Theory and Techniques shows that when relative velocity differences are below 0.2 m/s, low-cost radars (sample rate < 5 kHz, single Tx/Rx) cannot reliably separate peaks for two moving targets.
Micro-Doppler Analysis
Micro-Doppler captures detailed motion patterns like walking or arm swinging. Through short-time Fourier transform (STFT), it is theoretically possible to distinguish multiple individuals. However, this requires high sampling rates (>10 kHz) and fast DSP computation, which low-cost radars typically cannot provide.
Hardware and Firmware Limitations
DSP Processing Bottleneck
Entry-level radars often use low-frequency Cortex-M DSPs. Typical specifications:
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Sample rate: 1–5 kHz
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Range resolution: 0.5–1 m
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Angle resolution: not precise
These limitations lead to overlapping signals, target loss, and coordinate errors in multi-person scenarios.
API Constraints
Some radars only output the nearest target or a simple presence flag. Even with capable hardware, multiple coordinates are often inaccessible via the API. See our mmWave Radar Product Page for more details.
Multi-Target Applications and Requirements
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Office Space Management
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Requirement: real-time monitoring of meeting rooms and open offices
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Technical specs: range resolution < 0.3 m, angle resolution < 10°, support ≥5 targets
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Elderly Monitoring
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Requirement: fall detection and activity monitoring
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Specs: distinguish individuals, detect micro-movements, alarm delay <1 s
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Security Surveillance
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Requirement: track people in public spaces, factories, or malls
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Specs: multi-target coordinates, dense crowd tracking, false alarm <5%
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According to the European Telecommunications Standards Institute (ETSI), low-cost single-target radars achieve <70% accuracy in dense environments, recommending high-resolution MIMO or multi-sensor fusion solutions.
Solutions for Multi-Target Tracking
High-End MIMO Radar
MIMO radars use multiple transmit and receive antennas with beamforming, enhancing spatial and angular resolution for multiple target coordinates. Typical specs:
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Tx antennas: 4–8
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Rx antennas: 8–16
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Range resolution: 0.1–0.2 m
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Angle resolution: 3–5°
Suitable for office management, security, and healthcare applications. See High-Performance MIMO Radars.
Sensor Fusion
Combining mmWave radar with infrared, cameras, or ultrasonic sensors enables multi-target tracking even with low-cost hardware.
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Algorithms: Kalman filter + data association + micro-Doppler analysis
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Advantage: higher accuracy, reduced sensor limitations
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ETSI experiments show radar+infrared can reach 85–90% multi-target accuracy, ~20% higher than radar alone.
Software Optimization
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Micro-Doppler Classification: distinguish gait patterns
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Signal Clustering: separate targets via clustering algorithms
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Trajectory Prediction: estimate positions using historical data
These approaches are partially effective in low-density environments but limited under heavy traffic.
Conclusion
Low-cost mmWave radars have clear limitations in multi-person tracking due to DSP and API constraints. They are suitable for single-target or presence/motion detection, but high-density scenarios—such as office management, elderly monitoring, and security—benefit from high-end MIMO radar or sensor fusion.
Understanding radar principles, hardware limitations, and application needs helps developers design reliable multi-person tracking systems.
FAQ
Q1: Can low-cost radars detect multiple moving people?
A: They can detect motion but usually only output “presence” or nearest target coordinates.
Q2: What radar features are required for multi-target tracking?
A: High resolution, MIMO antenna arrays, strong DSP, and multi-target API support.
Q3: Can software algorithms alone achieve multi-target tracking?
A: Algorithms can partially separate targets using micro-Doppler or clustering, but sensor fusion is more reliable.
Q4: In which scenarios are low-cost radars sufficient?
A: Simple presence detection, single-target tracking, or environmental monitoring.