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Outbyte PC Repair FREERepair Windows errors before they cause bigger problemsFix Now →Outbyte Driver Updater FREEFix the driver behind crashes, sound loss and screen glitchesFind Drivers →mmWave presence radar detects people by transmitting radio waves and analyzing how objects reflect them back. Breathing, typing, fidgeting, or a small shift in posture changes the return over time. Signal-processing software can classify those subtle changes as evidence that someone is still present—even when they are not walking around.
That classification is an inference from radar measurements, not a camera-like image or a guarantee that the sensor has identified a person with certainty.
What the radar measures
A mmWave sensor sends radio-frequency energy into its surroundings and listens for reflections. The returned signal carries information about the scene. Texas Instruments describes radar returns as containing range (distance), velocity (speed and directionality), and angle (location) information about targets in its mmWave technical brief.
As a person moves, even slightly, the reflected signal changes. Walking typically creates a larger change; breathing or fidgeting creates smaller, repeated changes. The sensor analyzes changes over time rather than needing to form a visible picture of the person. It does not depend on visible light or a camera image.
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How small movements become a presence decision
The sensor and its processing software look for patterns in the changing return that satisfy configured detection rules. A person who stops walking may still produce detectable motion from breathing, typing, small head movements, or posture shifts. TI lists those as examples of micro-motions detectable by its IWRL6432AOP.
The software’s thresholds and state logic matter: a small signal change is not automatically classified as a person. For example, Infineon’s documented 60 GHz XENSIV BGT60TR13C implementation distinguishes micro-presence, macro-presence, and absence. Its application exposes settings such as maximum range and micro- and macro-motion thresholds. Other products may use different sensors, filters, thresholds, and state logic; the Infineon example is not a universal architecture.
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Why FMCW is used
One common radar technique is frequency-modulated continuous wave (FMCW). In Infineon’s example, the transmitter sends a continuous signal whose frequency changes over time. The system compares the transmitted signal with its reflection to derive measurements used for distance and motion detection, then applies its detection algorithm to decide which presence state fits.
The algorithm is part of the sensing system, not an optional detail. TI’s xWRL6432 motion-and-presence demo documentation describes an onboard processing chain that includes micro-Doppler classification and discrimination. A sensor’s hardware capabilities alone do not establish how well a particular product will classify subtle motion.
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How far can a mmWave presence sensor detect small movements?
There is no single range that applies to all mmWave presence radars. It depends on the sensor, algorithm, configured maximum range, installation, target position, and the movement being detected.
| Infineon BGT60TR13C application-brief claim | How to interpret it |
|---|---|
| Micro-motion such as breathing or typing: up to 4 m | Vendor-specific claim for the described solution; it is not a universal mmWave range. |
| Macro-motion: 5 m tested and qualified | Vendor-reported tested and qualified distance for that solution. |
| Macro-motion: up to 10 m | The brief says this distance was not tested and not qualified; do not treat it as validated performance. |
These figures come from Infineon’s presence-detection application brief. They describe a particular implementation and do not establish a general range for other sensors.
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What can affect detection
- Distance and configuration: Maximum range and motion thresholds can be configurable, as in Infineon’s documented implementation. A setting that is too restrictive may exclude a target; one that is too permissive may change what the algorithm treats as presence.
- Position and motion: The return depends on where the target is relative to the radar and how it moves. A subtle movement does not create the same return in every position or setup.
- Field of view and installation: Placement affects which parts of a space the radar can observe. The provided technical examples do not establish a universal guarantee for detection through every wall, enclosure, or material.
- Signal processing: Filters, classification methods, and state logic influence whether a small return change counts as presence.
How mmWave differs from a camera or PIR sensor
mmWave sensing uses reflected radio-frequency energy rather than visible light and does not require a camera image. The available radar measurements can include distance, velocity, and angle, while the presence decision depends on the implementation’s algorithm.
Infineon contrasts its radar solution with passive infrared (PIR) sensing for detecting micro-motion and integrating behind product enclosures. That is a vendor-specific comparison, not evidence that radar is universally better: the right approach depends on the needed sensitivity, location information, installation constraints, and the complete sensing system.
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A concrete example for builders
Infineon’s application note describes a 60 GHz FMCW presence-detection solution using the XENSIV BGT60TR13C and the KIT_CSK_BGT60TR13C development platform. It illustrates how configurable detection behavior and separate micro-presence, macro-presence, and absence states can turn radar measurements into an occupancy signal. The kit is a development platform for evaluation or prototyping, not necessarily a turnkey consumer occupancy sensor. See the Infineon application note for the implementation details.
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