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| import numpy as np
from scipy.signal import butter, filtfilt, find_peaks
class CPDDetector:
"""
儿童存在检测器
"""
def __init__(self, config):
self.config = config
self.range_fft_size = 256
self.doppler_fft_size = 64
def process_frame(self, adc_data):
"""
处理单帧数据
Args:
adc_data: ADC数据 (chirps, samples)
Returns:
detection: 检测结果
"""
range_fft = np.fft.fft(adc_data, n=self.range_fft_size, axis=1)
doppler_fft = np.fft.fft(range_fft, n=self.doppler_fft_size, axis=0)
detections = self.cfar_detector(np.abs(doppler_fft))
clusters = self.cluster_detections(detections)
vital_signs = self.extract_vital_signs(clusters)
return {
"occupancy": len(clusters) > 0,
"vital_signs": vital_signs,
"classification": self.classify(clusters, vital_signs)
}
def extract_vital_signs(self, clusters):
"""
提取生命体征（呼吸、心跳）
Args:
clusters: 检测到的目标簇
Returns:
vital_signs: 生命体征
"""
if len(clusters) == 0:
return {"breathing_rate": 0, "heart_rate": 0}
target = clusters[0]
phase_signal = target["phase_history"]
unwrapped = np.unwrap(phase_signal)
breathing_signal = self.bandpass_filter(unwrapped, 0.1, 0.5, fs=10)
heart_signal = self.bandpass_filter(unwrapped, 0.8, 2.0, fs=10)
breathing_rate = self.estimate_frequency(breathing_signal, fs=10)
heart_rate = self.estimate_frequency(heart_signal, fs=10)
return {
"breathing_rate": breathing_rate,
"heart_rate": heart_rate
}
def bandpass_filter(self, signal, low, high, fs):
"""
带通滤波
Args:
signal: 输入信号
low: 低频截止
high: 高频截止
fs: 采样频率
Returns:
filtered: 滤波后信号
"""
nyq = fs / 2
low_norm = low / nyq
high_norm = high / nyq
b, a = butter(2, [low_norm, high_norm], btype='band')
filtered = filtfilt(b, a, signal)
return filtered
def estimate_frequency(self, signal, fs):
"""
估计信号主频率
Args:
signal: 输入信号
fs: 采样频率
Returns:
frequency: 主频率 (Hz)
"""
fft = np.fft.fft(signal)
freqs = np.fft.fftfreq(len(signal), 1/fs)
magnitude = np.abs(fft)
peaks, _ = find_peaks(magnitude[:len(magnitude)//2])
if len(peaks) == 0:
return 0
peak_idx = peaks[np.argmax(magnitude[peaks])]
freq = freqs[peak_idx]
return abs(freq) * 60
def classify(self, clusters, vital_signs):
"""
分类：成人/儿童/空座
Args:
clusters: 目标簇
vital_signs: 生命体征
Returns:
classification: 分类结果
"""
if len(clusters) == 0:
return {"type": "empty", "confidence": 0.99}
breathing = vital_signs["breathing_rate"]
heart = vital_signs["heart_rate"]
if breathing > 30:
return {"type": "child", "confidence": 0.85}
else:
return {"type": "adult", "confidence": 0.80}
if __name__ == "__main__":
detector = CPDDetector({})
adc_data = np.random.randn(64, 256)
result = detector.process_frame(adc_data)
print(f"占用: {result['occupancy']}")
print(f"呼吸: {result['vital_signs']['breathing_rate']:.1f} 次/分钟")
print(f"心跳: {result['vital_signs']['heart_rate']:.1f} 次/分钟")
print(f"分类: {result['classification']['type']}")
|