Infinite Impulse Response Filter

The IIR high-pass filter is used in radar signal processing to suppress DC and low-frequency components,

primarily originating from static targets, while preserving dynamic target information.

 

 

 

 

 

 

 

1-1. Signal flow and Processing when IIR before Range FFT

It primarily affects range measurement by directly shaping the signal entering the Range FFT.

Velocity estimation is affected only indirectly,

through changes in range-bin SNR and stability, and this indirect influence is generally limited to moderate via range–Doppler coupling.

 

 

 

Removes DC and static-target clutter in fast-time I/Q signals, which mainly originate from stationary objects.
Improves the dynamic range of the Range FFT input by suppressing strong low-frequency components.
Stabilizes range peak detection, reducing false or biased peak responses caused by static reflections.
Reduced range resolution and group delay–induced range bias

 

 

 

 

 

 

 

 

1-2. Example cases

The b value is tuned to control the input dynamic range of the Range FFT and to stabilize range peak detection.

 

Target Category	Detailed State	a	b (Coefficient)	Configuration Characteristics
Human(Low-speed)	Ultra-fine Motion(Breathing/Sleep)	-1.0	0.992 ~ 0.996	Removes DC component only while preserving over 99% of phase information
	Static Presence (Seated)	-1.0	0.968 ~ 0.984	Balanced trade-off between stable DC removal and sensitivity
	Dynamic Activity (Walking)	-1.0	0.937 ~ 0.953	Strong motion signals allow faster DC removal
Vehicle(High-speed)	Urban Slow Driving/Parking	-1.0	0.906 ~ 0.937	Pre-suppression of strong near-field reflections (clutter)
	Normal Road Driving	-1.0	0.843 ~ 0.875	Vibration noise suppression to improve SNR
	High-speed Driving (Highway)	-1.0	0.750 ~ 0.812	Wide low-frequency cutoff for high-speed data processing

 

 

 

 

 

2-1. Signal flow and Processing when IIR is before Doppler FFT

It primarily affects velocity measurement by directly shaping the slow-time signal used for the Doppler FFT.

Range measurement is only weakly and indirectly influenced,

mainly through detection and association stages, with the impact typically very small.

 

 

 

 

 

Removes static-target clutter (0-Doppler components) in slow-time signals.
Flattens the Doppler background spectrum by suppressing dominant stationary returns.
Stabilizes CFAR thresholding and reduces false alarms.
Reduced sensitivity to low Doppler targets and potential velocity estimation distortion

 

 

 

 

 

 

 

 

2-2. Example Cases

The b parameter is adjusted according to the motion detection criteria.

 

Target Category	Detailed State (Scenario)	a	b (Coefficient)	Minimum Detectable Speed (Characteristics)
Human(Low-speed)	Micro-movement(Heartbeat/Breathing)	-1	0.995 ~ 0.999	Ultra-low speed (≤ 0.1 m/s) pass-through, very high precision
	Static Presence(Keyboard Typing)	-1	0.968 ~ 0.984	Extraction of subtle movements from a stationary person
	Walking & Direction Change	-1	0.921 ~ 0.953	Optimized clutter removal (tree leaves, static object residuals) during normal walking (~1 m/s)
	Vigorous Motion(Gestures)	-1	0.875 ~ 0.906	Removal of motion residuals from fast actions such as arm swinging
Vehicle(High-speed)	Urban Slow Driving(Stop & Go)	-1	0.843 ~ 0.875	Detection of initial acceleration of stop-and-go vehicles
	City Driving(Normal)	-1	0.750 ~ 0.812	Complete suppression of noise from surrounding buildings and roadside trees
	High-speed Driving(Highway)	-1	0.625 ~ 0.750	Strong suppression of all low-frequency components except high-speed targets