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Generally, the parking space recognition technology uses the ultrasonic sensor to obtain the position information of the side obstacle to determine the edge of the parking space. Due to the jump of the beam angle formed by the ultrasonic sensor and the obstacle during the measurement, and its inherent characteristics will bring random noise, which may not be directly obtained. The true exact value of the state variable. By establishing a suitable distance correction system state equation and observation equation, Kalman filtering algorithm is used to obtain the covariance of the moment from the ultrasonic sensor measurement value and random noise at time k-1 , and obtain the Kalman gain at time k from the measurement noise calculation. Then, the distance correction value of k+1 time is obtained by combining the measured value of the ultrasonic sensor at time k with the observation equation. The simulation results show that the absolute error after 150 iterations is 1.575cm, and the average correction time is only 0.028s, which is much smaller than the average correction error of the dual probe average method, the dual probe fusion method and the sensor error compensation method. It effectively reduces random noise interference, has good accuracy and real-time performance, and the filter measurement distance correction value is closer to the true value.