Abstract
Positioning asynchronous architectures based on time measurements are reaching growing importance in Local Positioning Systems (LPS). These architectures have special relevance in precision applications and indoor/outdoor navigation of automatic vehicles such as Automatic Ground Vehicles (AGVs) and Unmanned Aerial Vehicles (UAVs). The positioning error of these systems is conditioned by the algorithms used in the position calculation, the quality of the time measurements, and the sensor deployment of the signal receivers. Once the algorithms have been defined and the method to compute the time measurements has been selected, the only design criteria of the LPS is the distribution of the sensors in the three-dimensional space. This problem has proved to be NP-hard, and therefore a heuristic solution to the problem is recommended. In this paper, a genetic algorithm with the flexibility to be adapted to different scenarios and ground modelings is proposed. This algorithm is used to determine the best node localization in order to reduce the Cramér-Rao Lower Bound (CRLB) with a heteroscedastic noise consideration in each sensor of an Asynchronous Time Difference of Arrival (A-TDOA) architecture. The methodology proposed allows for the optimization of the 3D sensor deployment of a passive A-TDOA architecture, including ground modeling flexibility and heteroscedastic noise consideration with sequential iterations, and reducing the spatial discretization to achieve better results. Results show that optimization with 15% of elitism and a Tournament 3 selection strategy offers the best maximization for the algorithm.
Highlights
Global Positioning Systems (GNSS) have been traditionally used to guide vehicle navigation in outdoor environments
The high accuracy requirements in the positioning system demanded in new applications such as autonomous vehicle navigation (AGVs and Unmanned Aerial Vehicles (UAVs)) or tracking of robots in industrial plants, have led to a huge increase in local positioning systems (LPS) based on asynchronous positioning architectures, as the Asynchronous Time Difference of Arrival (A-Time Difference of Arrival (TDOA))
The intrinsic characteristics of the LPS systems cause a great dependence between the location of the sensors of the system and the degree of accuracy achieved in the positioning
Summary
Global Positioning Systems (GNSS) have been traditionally used to guide vehicle navigation in outdoor environments. Once the positioning architecture has been selected, along with the algorithms that allow for the calculation of the position [9,10,11], the only factor that allows the reduction of the global positioning error of the vehicles is the spatial distribution occupied by the sensors or satellites in space with respect to positioning targets This spatial distribution strongly affects the system accuracy by increasing the positioning errors due to the changes in the geometric properties of the intersection of the surfaces containing the possible locations of the targets in the space [11] -spheres in TOA systems and hyperboloids in TDOA systems. It is necessary to establish a methodology to optimize the location of the beacons in LPS systems, considering the special characteristics of these architectures
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