基于传感器矫正的汽车双重防盗系统设计

Auto Double Security System Design Based on Sensor Calibration

汽车防盗系统依靠报警设备进行被动的防盗,依靠GPS的网络型防盗受到信号覆盖区域的影响性较大,价格较高,防盗方式单一。为了提高防盗性能,提出一种PSO-BP传感器校正的汽车双重防盗系统设计方法,使用优化后的神经网络对安装在车辆上的速度传感器与超声波传感器进行输出校正,提高传感器信号的准确率,使用TC35i通信模块,建立GSM网络的防盗信号,加入了加速度传感器对汽车被盗后的速度进行网络跟踪与报警。实验证明,经过优化神经网络传感器校正后的汽车防盗系统不但在不同的环境下能够准确对汽车被盗进行准确报警,还能实现良好的人车交互能力,具有很强的使用价值。

The car alarm systems rely on alarm equipment for the prevention of burglary passively, and the network style prevention of burglary based on the GPS is subjects to larger influence from the signal coverage areas, the price is higher, and anti - theft mode is single. In order to improve the anti - theft performance, a dual anti - theft system design method based on PSO - BP sensor calibration was put forward. The optimized neural network was used to perform the output correction for the speed sensor and ultrasonic sensor installed on the vehicle to improve the ac- curacy of sensor signals. The TC35i communication module was used to establish the alarm signal based on the GSM network. An acceleration sensor was also added to carry out the network tracking of the speed of the car after it was stolen and alarming. Experimental results show that the car alarm system calibrated by the optimized neural network sensor can not only alarm for vehicle theft accurately in different circumstances, but also realize good man - car inter- action ability, having a strong value in use.