Vehicle speed estimation using acoustic wave patterns

We estimate a vehicle’s speed, wheelbase length, and its tire track length by jointly estimating its acoustic wave-pattern using a single passive acoustic sensor that records the vehicle’s drive-by noise. The acoustic wave-pattern is determined using three envelope shape (ES) components, which approximate the shape variations of the received signal’s power envelope. We incorporate the parameters of the ES components along with estimates of the vehicle engine RPM and the number of cylinders, and the vehicle’s loudness and speed to form a vehicle profile vector. This vector provides a compressed statistics that can be used for vehicle identification and classification. We also provide possible reasons for why some of the existing methods are unable to provide unbiased vehicle speed estimates using the same framework. The approach is illustrated using vehicle speed estimation and classification results obtained with field data

Analysis of vibration and acoustic signals for noncontact measurement of engine rotation speed

The non-contact measurement of engine speed can be realized by analyzing engine vibration frequency. However, the vibration signal is distorted by harmonics and noise in the measurement. This paper presents a novel method for the measurement of engine rotation speed by using the cross-correlation of vibration and acoustic signals. This method can enhance the same frequency components in engine vibration and acoustic signal. After cross-correlation processing, the energy centrobaric correction method is applied to estimate the accurate frequency of the engine's vibration. This method can be implemented with a low-cost embedded system estimating the cross-correlation. Test results showed that this method outperformed the traditional vibration-based measurement method.Web of Science203art. no. 68

Development and testing of a dual accelerometer vector sensor for AUV acoustic surveys

This paper presents the design, manufacturing and testing of a Dual Accelerometer Vector Sensor (DAVS). The device was built within the activities of theWiMUST project, supported under the Horizon 2020 Framework Programme, which aims to improve the efficiency of the methodologies used to perform geophysical acoustic surveys at sea by the use of Autonomous Underwater Vehicles (AUVs). The DAVS has the potential to contribute to this aim in various ways, for example, owing to its spatial filtering capability, it may reduce the amount of post processing by discriminating the bottom from the surface reflections. Additionally, its compact size allows easier integration with AUVs and hence facilitates the vehicle manoeuvrability compared to the classical towed arrays. The present paper is focused on results related to acoustic wave azimuth estimation as an example of its spatial filtering capabilities. The DAVS device consists of two tri-axial accelerometers and one hydrophone moulded in one unit. Sensitivity and directionality of these three sensors were measured in a tank, whilst the direction estimation capabilities of the accelerometers paired with the hydrophone, forming a vector sensor, were evaluated on a Medusa Class AUV, which was sailing around a deployed sound source. Results of these measurements are presented in this paper.European Union [645141]info:eu-repo/semantics/publishedVersio

The Impact of Acoustic Imaging Geometry on the Fidelity of Seabed Bathymetric Models

Attributes derived from digital bathymetric models (DBM) are a powerful means of analyzing seabed characteristics. Those models however are inherently constrained by the method of seabed sampling. Most bathymetric models are derived by collating a number of discrete corridors of multibeam sonar data. Within each corridor the data are collected over a wide range of distances, azimuths and elevation angles and thus the quality varies significantly. That variability therefore becomes imprinted into the DBM. Subsequent users of the DBM, unfamiliar with the original acquisition geometry, may potentially misinterpret such variability as attributes of the seabed. This paper examines the impact on accuracy and resolution of the resultant derived model as a function of the imaging geometry. This can be broken down into the range, angle, azimuth, density and overlap attributes. These attributes in turn are impacted by the sonar configuration including beam widths, beam spacing, bottom detection algorithms, stabilization strategies, platform speed and stability. Superimposed over the imaging geometry are residual effects due to imperfect integration of ancillary sensors. As the platform (normally a surface vessel), is moving with characteristic motions resulting from the ocean wave spectrum, periodic residuals in the seafloor can become imprinted that may again be misinterpreted as geomorphological information

Acoustic fatigue: Overview of activities at NASA Langley

A number of aircraft and spacecraft configurations are being considered for future development. These include high-speed turboprop aircraft, advanced vertical take-off and landing fighter aircraft, and aerospace planes for hypersonic intercontinental cruise or flight to orbit and return. Review of the acoustic environment expected for these vehicles indicates levels high enough that acoustic fatigue must be considered. Unfortunately, the sonic fatique design technology used for current aircraft may not be adequate for these future vehicles. This has resulted in renewed emphasis on acoustic fatigue research at the NASA Langley Research Center. The overall objective of the Langley program is to develop methods and information for design of aerospace vehicles that will resist acoustic fatigue. The program includes definition of the acoustic loads acting on structures due to exhaust jets of boundary layers, and subsequent determination of the stresses within the structure due to these acoustic loads. Material fatigue associated with the high frequency structural stress reversal patterns resulting from acoustic loadings is considered to be an area requiring study, but no activity is currently underway

Near bottom sediment characterization offshore SW San Clemente Island

Normal incidence, 23.5 kHz seafloor acoustic backscatter data and bottom video were measured with the Deep Tow instrument package of the Scripps Institution of Oceanography in 100 meter water depth south of San Clemente Island, CA. The collected data were processed using an echo envelopesediment characterization method, to derive geoacoustic parameters such as particle mean grain size and the strength of the power law characterizing the roughness energy density spectrum of thesediment-water interface. Two regions, sand and silt, were selected based on available ground truth, perceived along-track sediment homogeneity, data quality and tow fish stability. Distinction between sand and fine grain sediments can be accomplished by creation of feature vectors comprised of mean grain size (MΦ) and interface roughness spectral strength (w2). Estimates for mean grain size and roughness spectral strength (MΦ, w2) were (1.5, 0.0095) for sand, and (6.7, 0.0033) for silt, where MΦ is expressed in PHI units, and w2 has units cm4. These results are consistent with local ground truth measurements and illustrate the potential of this sediment characterization method in survey mode

Index to 1984 NASA Tech Briefs, volume 9, numbers 1-4

Short announcements of new technology derived from the R&D activities of NASA are presented. These briefs emphasize information considered likely to be transferrable across industrial, regional, or disciplinary lines and are issued to encourage commercial application. This index for 1984 Tech B Briefs contains abstracts and four indexes: subject, personal author, originating center, and Tech Brief Number. The following areas are covered: electronic components and circuits, electronic systems, physical sciences, materials, life sciences, mechanics, machinery, fabrication technology, and mathematics and information sciences