In the past years, algorithms for 3D shape tracking using radial functions in spherical coordinates represented with different methods have been proposed. However, we have seen that mainly measurements from the lateral surface of the target can be expected in a lot of dynamic scenarios and only few measurements from the top and bottom parts leading to an error-prone shape estimate in the top and bottom regions when using a representation in spherical coordinates. We, therefore, propose to represent the shape of the target using a radial function in cylindrical coordinates, as these only represent regions of the lateral surface, and no information from the top or bottom parts is needed. In this paper, we use a Fourier-Chebyshev double series for 3D shape representation since a mixture of Fourier and Chebyshev series is a suitable basis for expanding a radial function in cylindrical coordinates. We investigate the method in a simulated and real-world maritime scenario with a CAD model of the target boat as a reference. We have found that shape representation in cylindrical coordinates has decisive advantages compared to a shape representation in spherical coordinates and should preferably be used if no prior knowledge of the measurement distribution on the surface of the target is available.
In this paper, approximating the shape of a sailing boat using elliptic cones is investigated. Measurements are assumed to be gathered from the target's surface recorded by 3D scanning devices such as multilayer LiDAR sensors. Therefore, different models for estimating the sailing boat's extent are presented and evaluated in simulated and real-world scenarios. In particular, the measurement source association problem is addressed in the models. Simulated investigations are conducted with a static and a moving elliptic cone. The real-world scenario was recorded with a Velodyne Alpha Prime (VLP-128) mounted on a ferry of Lake Constance. Final results of this paper constitute the extent estimation of a single sailing boat using LiDAR data applying various measurement models.
Dissipation of heat can be a major challenge when applying sensor systems outdoors under varying environmental conditions. Typically, complex software and knowledge is needed to optimize thermal management. In this paper it is shown how the thermal optimization of a LiDAR (light detection and ranging) sensor can be performed efficiently. This approach uses standard CAD (computer aided design) software, which is readily available, and saves time and cost as the thermal design can be optimized before experimental realisation. A four-step process was developed and realized: (i) Measurement of the thermal energy distribution of the current sensor design; (ii) Simulation of the time-dependant thermal behaviour using standard CAD software; (iii) Simulation of a thermally optimized design. This was compared quantitatively with the original design and was also used for verification of sufficient increase in heat dissipation; (iv) Experimental realisation and verification of the optimized design. It could be shown that the optimized prototype shows significantly improved thermal behaviour in accordance with the predictions from the simulations. The new LiDAR sensor shows lower heat generation and optimized dissipation of thermal energy which proofs the applicability of the approach to complex sensors.