Browsing by Subject "Range measurement"

Now showing 1 - 4 of 4

Open Access
Comparison of two methods of surface profile extraction from multiple ultrasonic range measurements
(Institute of Physics Publishing, 2000) Barshan, B.; Backent, D.
Two novel methods for surface profile extraction based on multiple ultrasonic range measurements are described and compared. One of the methods employs morphological processing techniques, whereas the other employs a spatial voting scheme followed by simple thresholding. Morphological processing exploits neighbouring relationships between the pixels of the generated arc map. On the other hand, spatial voting relies on the number of votes accumulated in each pixel and ignores neighbouring relationships. Both approaches are extremely flexible and robust, in addition to being simple and straightforward. They can deal with arbitrary numbers and configurations of sensors as well as synthetic arrays. The methods have the intrinsic ability to suppress spurious readings, crosstalk and higher-order reflections, and process multiple reflections informatively. The performances of the two methods are compared on various examples involving both simulated and experimental data. The morphological processing method outperforms the spatial voting method in most cases with errors reduced by up to 80%. The effect of varying the measurement noise and surface roughness is also considered. Morphological processing is observed to be superior to spatial voting under these conditions as well.
Open Access
Fast processing techniques for accurate ultrasonic range measurements
(Institute of Physics Publishing, 2000) Barshan, B.
Four methods of range measurement for airborne ultrasonic systems - namely simple thresholding, curve-fitting, sliding-window, and correlation detection - are compared on the basis of bias error, standard deviation, total error, robustness to noise, and the difficulty/complexity of implementation. Whereas correlation detection is theoretically optimal, the other three methods can offer acceptable performance at much lower cost. Performances of all methods have been investigated as a function of target range, azimuth, and signal-to-noise ratio. Curve fitting, sliding window, and thresholding follow correlation detection in the order of decreasing complexity. Apart from correlation detection, minimum bias and total error is most consistently obtained with the curve-fitting method. On the other hand, the sliding-window method is always better than the thresholding and curve-fitting methods in terms of minimizing the standard deviation. The experimental results are in close agreement with the corresponding simulation results. Overall, the three simple and fast processing methods provide a variety of attractive compromises between measurement accuracy and system complexity. Although this paper concentrates on ultrasonic range measurement in air, the techniques described may also find application in underwater acoustics.
Open Access
Improved range estimation using simple infrared sensors without prior knowledge of surface characteristics
(Institute of Physics Publishing Ltd., 2005) Yüzbaşioglu, Ç.; Barshan, B.
This paper describes a new method for position estimation of planar surfaces using simple, low-cost infrared sensors. The intensity data acquired with infrared sensors depend highly on the surface properties and the configuration of the sensors with respect to the surface. Therefore, in many related studies, either the properties of the surface are determined first or certain assumptions about the surface are made in order to estimate the distance and the orientation of the surface relative to the sensors. We propose a novel method for position estimation of surfaces with infrared sensors without the need to determine the surface properties first. The method is considered to be independent of the type of surface encountered since it is based on searching for the position of the maximum value of the intensity data rather than using absolute intensity values which would depend on the surface type. The method is verified experimentally with planar surfaces of different surface properties. An intelligent feature of our system is that its operating range is made adaptive based on the maximum intensity of the detected signal. Three different ways of processing the intensity signals are considered for range estimation. The absolute mean range error for the method resulting in the lowest errors is 0.15 cm over the range from 10 to 50 cm. The cases where the azimuth and elevation angles are nonzero are considered as well. The results obtained demonstrate that infrared sensors can be used for localization to an unexpectedly high accuracy without prior knowledge of the surface characteristics.
Open Access
Map building with multiple range measurements using morphological surface profile extraction
(IEEE, Piscataway, NJ, United States, 1999) Barshan, B.; Başkent, D.
A novel method is described for surface profile extraction based on morphological processing of multiple range sensor data. The approach taken is extremely flexible and robust, in addition to being simple and straightforward. It can deal with arbitrary numbers and configurations of range sensors as well as synthetic arrays. The method has the intrinsic ability to suppress spurious readings, crosstalk, and higher-order reflections, and process multiple reflections informatively. The essential idea of this work - the use of multiple range sensors combined with morphological processing - can be applied to different physical modalities of range sensing of vastly different scales and in many different areas. These may include radar, sonar, robotics, optical sensing and metrology, remote sensing, ocean surface exploration, geophysical exploration, and acoustic microscopy.