tb_range_doppler_map — 2D typed op

資料種類:beatcubeimage

呼叫:fullseye.apply(img, "tb_range_doppler_map", a=0.5, b=0.5)(2-D 的模型是一張圖 + 兩個純量旋鈕 a,b∈[0,1])

*無圖: 該運算子以 beatcube 為輸入。從影像開始的 Studio 程式無法到達該型別,請參見下方的可執行範例。*

用法

拍頻立方體的二維 FFT -> `(n_doppler, n_range)` 幅度圖。

> 以下的詳細說明為原文 —— 摘要與標題已翻譯。

Fast time transforms to range (last axis, not shifted: bin `j` is

`j * c*f_s/(2*S*N_s)` metres, and a physical range is always positive so

the whole `[0, f_s)` band is used). Slow time transforms to velocity

(middle axis, `fftshift`ed so the map is centred on zero velocity: bin

`i is (i - N_c//2) * lambda/(2*N_c*T_c)` metres per second, positive =

receding).

The antenna axis is collapsed by *combine*: `"incoherent"` (default) is the

mean of the magnitudes, which is angle independent and therefore the

right default for detection; `"coherent"` is the magnitude of the mean,

i.e. a beam pointed at boresight, which attenuates an off-boresight target on

purpose. `antenna=k uses element k` alone. For a single-element cube

all three agree exactly.

`normalize=True divides by N_c * N_s`, so a bin-centred target of

amplitude `a peaks at exactly a` (measured: 1.0 for a unit target,

absolute error 0.0). The default `False` keeps the raw FFT magnitude.

No window is applied — compose :func:fmcw_window_apply first if you want

one. The output is a plain 2-D float64 array, so every 2-D operator in

Fullseye (threshold, morphology, labelling, blob measurement — the pieces a

CFAR detector is made of) applies to it directly.

Raises `ValueError`: a real-valued cube (it would put a mirror ghost of

every target at a fabricated range), fewer than 2 chirps or 2 samples, an

out-of-range *antenna* index, an unknown *combine*, a cube over the element

cap, an FFT that overflows to NaN, or NaN/Inf on the way in.

Typed bridge of the rangedoppler op `range_doppler_map into the 2-D evolution registry: the same implementation, called under the op(v, a, b) convention. This op has no tunable parameter; a and b` are unused.

參考(範例資料・文獻)

• 範例資料目錄(下載 URL / 授權) —— 2-D 用 skimage.data(BSD/公有領域)加合成圖,3-D 給出真實資料源(Stanford/PDS 等)的下載 URL。

• 運算子來歷與參考文獻 —— 該運算子族所依據的研究/方法出處。

可執行的範例(實際呼叫該運算子並已驗證的樣例)

• (尚無)

型別可銜接的下一個運算子(可接受 image 作為輸入)

identity · gaussian · mean_box · bilateral · unsharp · median · min_filter · max_filter

同類別(typed)

tb_points_to_voxel · tb_estimate_point_normals · tb_iss_keypoints · tb_angle_3points · tb_project_points · tb_render_point_depth · tb_statistical_outlier_removal · tb_radius_outlier_removal


*Provenance: ops.py — 2D 運算子登記表。本條目由 tools/opdocs.py md 自動產生(請勿手動編輯)。*

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