fmcw_window_apply — RANGEDOPPLER process op

Datenarten: beatcubebeatcube

Aufruf: import rangedoppler; rangedoppler.fmcw_window_apply(cube, window='hann', axis='range') (oder opsrangedoppler.get("fmcw_window_apply"))

Verwendung

Wendet ein periodisches Fenster entlang der Entfernungs- und/oder Doppler-Achse eines Beat-Würfels an.

> Die ausführliche Beschreibung unten ist der Originaltext — Zusammenfassung und Überschriften sind übersetzt.

The sidelobes of a rectangular (unwindowed) transform are -13.3 dB, so a

strong target buries a weak one 20 dB down at a completely different range.

Windowing trades main-lobe width for sidelobe level; the published figures

(Harris 1978, Table 1) and the levels measured in this repository on a

single bin-centred target are:

========== ============== ============== ==================

window published PSL measured PSL measured -3 dB lobe

========== ============== ============== ==================

rect -13.3 dB -13.25 dB 0.885 bin

hann -31.5 dB -31.47 dB 1.438 bin

hamming -42.7 dB -42.45 dB 1.301 bin

blackman -58.1 dB -58.11 dB 1.641 bin

========== ============== ============== ==================

Measured by transforming each window on its own with 2^18-point zero padding

and taking the highest lobe past the first null — that *is* the definition of

peak sidelobe level, so these are the module's own numbers, not copied ones.

Hamming lands 0.25 dB off the published figure because the published one is

for the optimal 0.53836/0.46164 pair; the 0.54/0.46 coefficients written here

are the textbook ones and this is what they actually give.

What it buys, measured end to end: a target 45 dB below a strong one, seven

range bins away, is undetectable unwindowed (its cell sits 24.6 dB down

in the leakage skirt and is not even a local maximum) and becomes a clean

local maximum at -43.6 dB with `hann`. That comparison is step 4 of

`examples/fmcw_range_doppler.py`.

*axis* is named by role — `"range"` (fast time, the last axis),

`"doppler" (slow time, the middle axis) or "both"` — never by number,

because a transposed cube is the mistake this naming is defending against.

The window is *not* folded into :func:range_doppler_map: keeping it a

separate op is what lets the sidelobe table above be measured as a

difference, and keeps the transform op a pure 2-D FFT.

Returns a new complex cube of the same shape. Raises `ValueError` on a

real-valued or malformed cube, or an unknown *window* / *axis*.

Ausführlicher Anwendungsleitfaden

Leitfaden zur Familie fmcw_range_doppler

Referenzen (Beispieldaten, Literatur)

• Katalog der Beispieldaten (Download-URLs / Lizenzen) — 2-D nutzt skimage.data (BSD/Public Domain) plus synthetische Bilder, 3-D nennt Download-URLs echter Datenquellen (Stanford, PDS, …).

• Herkunft und Literatur der Operatoren — die Quellen der Forschung/Verfahren, auf denen diese Operatorfamilie beruht.

• Der kanonische Algorithmus (Autor, Jahr) und seine Anwendungen stehen im Familienleitfaden oben.

Ausführbare Beispiele (verifizierte Samples, die diesen Operator wirklich aufrufen)

fmcw_range_dopplerpy -3.11 examples/fmcw_range_doppler.py

Typkompatible Folge-Operatoren (nehmen beatcube als Eingabe)

range_doppler_map · fmcw_range_profile · beamform_delay_sum · beamform_doa

Gleiche Kategorie (process)

range_doppler_map · range_doppler_peaks · fmcw_range_profile


*Provenance: rangedoppler.py — RANGEDOPPLER Operator-Registry. Diese Notiz wird von tools/opdocs.py md erzeugt (nicht von Hand bearbeiten).*

© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.