Skip main navigation

Cookies Notification

We use cookies on this site to enhance your user experience. By continuing to browse the site, you consent to the use of our cookies. Learn More
×

System Upgrade on Tue, May 28th, 2024 at 2am (EDT)

Existing users will be able to log into the site and access content. However, E-commerce and registration of new users may not be available for up to 12 hours.
For online purchase, please visit us again. Contact us at customercare@wspc.com for any enquiries.

SEARCH GUIDE  Download Search Tip PDF File

  • articleNo Access

    SPATIAL MAP BUILDING USING FAST TEXTURE ANALYSIS OF ROTATING SONAR SENSOR DATA FOR MOBILE ROBOTS

    This paper presents a novel, fast algorithm for accurate detection of the shape of targets around a mobile robot using a single rotating sonar element. The rotating sonar yields an image built up by the reflections of an ultrasonic beam directed at different scan angles. The image is then interpreted with an image-understanding approach based on texture analysis. Several important tasks are performed in this way, such as noise removal, echo correction and restoration. All these processes are obtained by estimating and restoring the degree of texture continuity. Texture analysis, in fact, allows us to look at the image on a large scale thus giving the possibility to infer the overall behavior of the reflection process. The algorithm has been integrated in a mobile robot. However, the algorithm is not suitable for working during the mobile robot movement, rather it can be used during the period when the robot stays in a fixed position.

  • articleNo Access

    Time Frequency Wavenumber Analysis of Surface Waves and Signal Enhancement Using S-Transform

    Highly dispersive surface waves resulting from the combination of strong lateral seafloor heterogeneities, shallow water depths and hard sea bottom severely degrade seismic reflection data quality. Considering that seismic signals are nonstationary and surface waves have various spectra over time, we proposed S-transform-based time frequency wavenumber analysis technique which allows the dynamic analysis of spectrum over time. The data is first transformed from the time-space domain to the time-wavenumber domain through one-dimensional Fourier transform over the spatial variable, then the variable-factor S-transform is applied over time. Nonstationary filtering is then designed to identify and separate surface waves in complex wavefields, based on its low frequency and low velocity properties, in the time-frequency-wavenumber (TFK) domain. Application to field data illustrates that with this technique, not only is the surface wave effectively suppressed, but also the reflective signals are enhanced, which confirm the validity of the method.