用scipy fft计算信号的自相关与直接计算得到的结果不同

import numpy as np
from scipy.fft import fft, ifft

def autocorrelation_fft(signal):
    signal = np.asarray(signal)
    N = len(signal)
    padded_signal = np.pad(signal, (0, N), 'constant')
    spectrum = fft(padded_signal)
    autocorr_spectrum = spectrum * np.conj(spectrum)
    autocorr = ifft(autocorr_spectrum)
    return autocorr[:N].real

def direct_autocorrelation(signal):
    result = np.correlate(signal, signal, mode='full')
    return result[len(result)//2:]

# 示例信号
signal = np.random.rand(100)

# 计算自相关
fft_result = autocorrelation_fft(signal)
direct_result = direct_autocorrelation(signal)

print("FFT 自相关结果:", fft_result)
print("直接计算自相关结果:", direct_result)

signal = np.random.rand(100).astype(np.float64)

from scipy.signal import windows

window = windows.hann(len(signal))
signal_windowed = signal * window