MOBILE ROBOT SONAR FOR TARGET LOCALIZATION AND CLASSIFICATION
MOBILE ROBOT SONAR FOR TARGET LOCALIZATION AND CLASSIFICATION
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DOI：
10.1177/027836499501400401
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发表时间：
1995-08-01
影响因子：
9.2
通讯作者：
KUC, R
中科院分区：
文献类型：
--
作者：
KLEEMAN, L;KUC, R
提出了一种新型声纳阵列，可用于移动机器人室内环境的定位和测绘。该超声波传感器对二维多目标进行定位分类，最大可达8m，考虑温湿度的影响，系统精度可达1 mm以内，在静止空气中可分辨出距离为10 mm的0.1度目标。推导出这些测量的误差协方差矩阵，以允许与其他传感器融合。从统计学上将目标分为四种反射器类型：平面、角点、边缘和未知。本文证明了两个发射器和两个接收器是区分平面、角点和边缘的必要条件和充分条件。传感器阵列具有该最小数量的发射器和接收器。该方法采用了一种新的设计方法，使得多个目标的不同接收器回波关联的对应问题最小化，并使用脉冲发射、接收、空气吸收和色散的线性滤波模型来生成一组作为距离和方位角函数的回波模板。根据回波与模板的最大互相关来估计最佳回波到达时间。模板的使用还允许抑制重叠回波和干扰。对噪声特性进行建模，以用于目标距离和方位的最大似然估计。给出了实验结果以验证假设和对传感器的表征。
A novel sonar array is presented that has applications in mobile robotics for localization and mapping of indoor environments. The ultrasonic sensor localizes and classifies multiple targets in two dimensions to ranges of up to 8 m. By accounting for effects of temperature and humidity, the system is accurate to within 1 mm and 0.1 degrees in still air Targets separated by 10 mm in range can be discriminated. The error covariance matrix for these measurements is derived to allow fusion with other sensors. Targets are statistically classified into four reflector types: planes, corners, edges, and unknown.This article establishes that two transmitters and two receivers are necessary and sufficient to distinguish planes, corners, and edges. A sensor array is presented with this minimum number of transmitters and receivers. A novel design approach is used such that the receivers are closely spaced so as to minimize the correspondence problem of associating different receiver echoes from multiple targets.A linear filter model for pulse transmission, reception, air absorption, and dispersion is used To generate a set of templates for the echo as a function of range and bearing angle. The optimal echo arrival lime is estimated from the maximum cross-correlation of the echo with the templates. The use of templates also allows overlapping echoes and disturbances to be rejected. Noise characteristics are modeled for use in the maximum likelihood estimates of target range and bearing. Experimental results are presented to verify assumptions and characterize the sensor.