基于多特征融合的驾驶员状态检测的实现

摘要

针对驾驶员状态检测和提取特征单一化以及检测设备成本过高的缺陷,提出了一种多特征融合的驾驶员状态的实现.该系统以内置DSP芯片的STM32L4低功耗单片机为核心,首先通过SON1303、MPU6050等传感器实时采集,分别获取人的脉搏、加速度、角速度以及姿态角特征参数;其次,脉搏调用DSP库实现快速傅里叶变换(FFT),利用切比雪夫窗口设计滤波器提取频谱;最后,通过驾驶员状态良好、疲劳、分心以及紧张频谱分析,定义第一主峰B以及频谱比K,融合B、K、姿态角、加速度、角速度等特征实现对驾驶员状态的判断.通过实验测试,该系统具有抗干扰强、低成本等特点,可以广泛应用于驾驶员状态检测,便于ADAS技术推广.%Aiming at the simplification of the driver's state detection,feature extraction,and the high cost of detecting equipment,the implementation of driver's state detection based on multiple feature fusion isproposed.The system adopts STM32L4 DSP chip as the core control.Firstly,characteristics such as pulse,acceleration,angular velocity,attitude angle and human body temperature are acquired and processed by SON1303,MPU6050.Secondly,for pulse,DSP library is called to implement FFT and Chebyshev filter is used to extract the frequency spectrum.Finally,a method via analyzing the frequency spectrum of the driver's state,tiredness,distraction and tension,defining the first main peak B and spectral ratio K,and fusing these characteristics as B,K,attitude angle,acceleration and angular velocity can judge driver's states effectively.Experiments show that the system has the characteristics of strong anti-interference,low cost,etc.It can be widely used in the state detecting of divers,and it can promote the popularization of ADAS.