PERFORMANCE OF SITE VELOCITY PREDICTION IN SUNDALAND

Global Positioning System (GPS) technique has been extensively implemented in determination of crustal deformation globally. With the ability of providing solution up to milimeter (mm) level, this technique has proven to provide a precise estimate of site velocity that represents the actual motion of tectonic plate over a period. Therefore, this study aims to evaluate the site velocity estimation from GPS-derived daily position of station, respective to the global plate motion model and predicted site velocity via Least-Squares Collocation (LSC) method within the tectonically active region of Sundaland. The findings have indicated that stations with precise velocity estimates were consistent with global plate model and predicted velocity, with velocity residuals of 5 mm – 10 mm. However, stations that were severely impacted by continuous earthquake events such as in Sumatra were believed to be induced by the impact with consistently large velocity residuals up to 37 mm. Following the outcomes, this study has provided an insight on the post-seismic decay period plate motion which are induced by continuous tectonic activities respective to modelled plate motion.

Vehicle Lateral Velocity Estimation Based on Long Short-Term Memory Network

Lateral velocity is an important parameter to characterize vehicle stability. The acquisition of lateral velocity is of great significance to vehicle stability control and the trajectory following control of autonomous vehicles. Aiming to resolve the problems of poor estimation accuracy caused by the insufficient modeling of traditional model-based methods and significant decline in performance in the case of a change in road friction coefficient, a deep learning method for lateral velocity estimation using an LSTM, long-term and short-term memory network, is designed. LSTM can well reflect the inertial characteristics of vehicles. The training data set contains sensor data under various working conditions and roads. The simulation results show that the prediction model has high accuracy in general and robustness to the change of road friction coefficient.

On the Geometric Featureless Visual Velocity of UGV in an Agriculture Scale

The paper discusses a camera-based velocity estimation for unmanned ground vehicles in an agriculture scale. The proposed concept-based method does not require any geometric feature and focuses on a mapping between the captured images only. The paper provides three pilot experiments. First, we check an assumption of the proposed concept by a field experiment. Second, we check the verification by a set of numerical and laboratory experiments. Third, we check the verification by the field experiment. In the sense that the existence and sensitivity of a representation of the mapping are verified experimentally, the feasibility of the proposed concept is confirmed.

A small vessel detection using a co-located multi-frequency FMCW MIMO radar

Small vessels detection is a known issue due to its low radar cross section (RCS). An existing shore-based vessel tracking radar is for long-distance commercial vessels detection. Meanwhile, a vessel-mounted radar system known for its reliability has a limitation due to its single radar coverage. The paper presented a co-located frequency modulated continuous waveform (FMCW) maritime radar for small vessel detection utilising a multiple-input multiple-output (MIMO) configuration. The radar behaviour is numerically simulated for detecting a Swerling 1 target which resembles small maritime’s vessels. The simulated MIMO configuration comprised two transmitting and receiving nodes. The proposal is to utilize a multi-frequency FMCW MIMO configuration in a maritime environment by applying the spectrum averaging (SA) to fuse MIMO received signals for range and velocity estimation. The analysis was summarised and displayed in terms of estimation error performance, probability of error and average error. The simulation outcomes an improvement of 2.2 dB for a static target, and 0.1 dB for a moving target, in resulting the 20% probability of range error with the MIMO setup. A moving vessel's effect was observed to degrade the range error estimation performance between 0.6 to 2.7 dB. Meanwhile, the proposed method was proven to improve the 20% probability of velocity error by 1.75 dB. The impact of multi-frequency MIMO was also observed to produce better average error performance.