Data Sheet

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K-LD7
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data sheet 12/2020 - Revision B
Page 7 / 23
Raw targets and tracking filter
A real object generates not only one raw target point.
A moving person for example generates several
raw target points with different speeds and different
distances created by the torso, the legs and the arms.
This generates a so called point cloud of different raw
targets from one object. Depending on the environ-
ment where the sensor is used it will also see more or
less reflexions generated by the moving object. The
number of raw targets can be controlled by adjusting
the threshold offset which is described in more detail
in chapter Threshold offset on page 10.
Micro detection
The micro detection is a feature to detect very slow
speeds in short range applications. It takes advantage
of an algorithm that analyses the DC bin of theFFT
to detect very slow speeds. The micro detection
is independent from the normal detection algorithm
and always enabled. It is available in the detection
data structure DDAT and can be used to retrigger
thehold time.
Further it is possible to adjust the sensitvity of the
micro detection over the parameter „Micro detection
sensitvity“.
To get a more usable output the sensor features a
tracking filter to cluster and track the dominant target
based on the raw targets. The filter includes a sup-
pression of reflexions, vibrations and interferences
and can also predict temporary lost targets what
generates a smooth output.
The tracking filter can be adapted to various applications
via the parameters Tracking filter type and Vibration sup-
pression which is described in more detail in chapter Tra-
cking on Page 10.
Figure 7: Raw targets vs. tracked target
The sensitivity of the micro detection depends
on the used speed range setting. To get the
best results always set the speed range first
before adjusting the micro detection sensitivity
parameter.
The filter can track only one target up to a dis-
tance of 30m.