F2008-05-038
A Method of Enhancing the Detection Range of Ultrasonic Sensors in Pre-Crash Applications
A conventional ultrasonic sensor for automotive applications can detect a target only in a short range of 2~3 m because of the requirements for a compact, waterproof package. Therefore, it can only be used for user-friendly systems like a parking assist system or a rear sonar system. For pre-crash applications, generally proposed sensors like stereo cameras, radar or lidar are able to detect obstacles at long distances, but they are much more expensive than ultrasonic sensors. This paper proposes a method for enhancing the detection range of ultrasonic sensors, making them applicable to pre-crash systems. The time-of-flight method is one of the typical techniques used for measuring distance with ultrasonic sensors. The distance to the target can be calculated from the time difference between the transmitted pulse and the received pulse. The relative speed of the received pulse is found from the Doppler frequency calculated with a fast Fourier transform. However, a wave reflected from a far distance is quite difficult to detect and to calculate its distance and relative speed because it is corrupted by surrounding random disturbance noise, such as echoes from the ground. For pre-crash applications, the sensor needs to detect a target at farther distances because the target moves faster than the objects detected by conventional user-friendly systems. Hence, we developed a method of detecting and calculating a reflected signal masked by random noise in order to increase the detection range of conventional ultrasonic sensors. This method uses a pseudo-Wigner distribution (p-WD)-based likelihood function. In a preliminary experiment, the proposed method was applied to observation data obtained experimentally with an actual ultrasonic sensor. First, the p-WD of the reflected wave of the target at a near distance so that it does not suffer from any noise was calculated as a reference signal (Fig. 1). Then, using the whole length of the noisy observation data, the p-WD was calculated off-line to obtain the log-likelihood ratio function. The reflected wave was detected by maximizing the p-WD-based likelihood function with respect to the parameters related to the time-delay and the frequency (Fig. 2). The distance was calculated from the time-delay and the relative speed from the frequency. In addition, we developed advanced ultrasonic sensor hardware. A conventional ultrasonic sensor can only detect stationary or slowly moving obstacles. However, for pre-crash applications, the sensor has to detect objects moving at high speed, which means the receiver must be able to consider the Doppler effect of received echoes. We developed a high-power transmitter and modified the receiving circuit in consideration of the frequency characteristics. The newly developed sensor has wide detection sensitivity for target speeds from 0 km/h to 40 km/h. As a result of modifying and optimizing the transmitter, receiver and signal processing based on the p-WD-based method for received reflected waves, the new ultrasonic sensor can be used for pre-crash applications.
This abstract is supplemented by a PDF, which can be viewed here.
Session: Sensor Systems