Abstract
Velocity is vital information for navigation and oceanic engineering. Coherent Doppler sonar is an accurate tool for velocity measurement, but its use is limited due to velocity ambiguity. Velocity measured by frequency shift has no velocity ambiguity, yet its measurement error is larger than that of coherent Doppler sonar. Therefore, coherent Doppler sonar assisted by frequency shift is used to accurately measure velocity without velocity ambiguity. However, the velocity measured by coherent Doppler sonar assisted by frequency shift is affected by impulsive noise. To decrease the impulsive noise, Kalman filter and linear prediction are proposed to improve the velocity sensing accuracy. In this method, the Kalman filter is used to decrease measurement error of velocity measured by frequency shift, and linear prediction is used to remove the impulsive noise generated by a wrong estimate of the integer ambiguity. Lab-based experiments were carried, and the results have shown that coherent Doppler sonar assisted by frequency shift, Kalman filter and linear prediction can provide accurate and precise velocity with short time delay in a large range of signal to noise ratio.
Highlights
Velocity is vital information for ships and underwater vehicles, playing an important role in navigation and oceanic engineering
At the 2000 International Convention for the Safety of Life at Sea (SOLAS), vessels more than 50,000 gross tons were recommended to be equipped with two axes speed and distance measurement equipment (SDME) to provide velocity information [1]
Electro-magnetic (EM) log, inertial navigation system (INS), Global Positioning System (GPS) and Doppler sonar systems are used to measure the velocity of moving vessels at sea
Summary
Velocity is vital information for ships and underwater vehicles, playing an important role in navigation and oceanic engineering. The Doppler sonar system can measure the velocity of objects both on the sea surface and in the water. Conventional Doppler sonar measured velocity using frequency shift has been wildly used as a basic device installed on vessels to provide velocity information. CHDS assisted by frequency shift (CHDSF) [16,17] was proposed to provide an accurate velocity without velocity ambiguity. A CHDS assisted by frequency shift, Kalman filter and linear prediction is proposed to provide accurate and precise velocity. To decrease the impulsive noise in CHDSF, a data processing method using the Kalman filter and linear prediction is introduced.
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