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Industrial PhD Optimal data fusion for aerial navigation 
XXXVIII Cycle
(starting Nov. 2022)
The research, funded and conducted with Leonardo SpA, regards the flight region at low altitudes (below 150 m) above urban areas, in which it is expected the highest impact and risk of UAVs use in both the typical flight configurations, i.e. Remotely Piloted Aircraft Systems and Autonomous Systems (with remote monitoring). In this context, the evolution of Unmanned Aircraft System Traffic Management (UTM) systems represents a fundamental step towards the safe and reliable application of this technology and the full exploitation of its potential in terms of new services and business cases. Accurate localization of UAVs is obviously one of the fundamental functions for safe and efficient navigation in assisted or autonomous UAVs and UTM systems.
Activity and objectives
The research and development activity are expected to focus on the following topics, organized in 3 areas: theory, software and hardware.
- [Theory] Problem formulation and optimization of the fusion among the available sources for the position estimate given a constraint on the minimum level of accuracy. The optimization does not regard just the different sources but also, within each source, the selection of the anchors exploited by the positioning process (when multilateration is used), in which the geometric factor plays a fundamental role.
- [Theory] Optimization of the distribution of the computational resources, in case of wireless connectivity. Where to perform the computational process is a relevant issue for its impact on latency. Several scenarios are considered, including the support of edge nodes, capable of a fast response to the UAV.
- [Software] Implementation of algorithms for the adaptive, automatic selection of the sources / measures. The experience in the optimization of cost functions with high number of variables and combinatorial nature allows us to anticipate that a sub-optimal solution is necessary. This opens a wide range of options in the search of methods that, maintaining a satisfactory performance w.r.t. full complexity solution, respond to the necessity of fast, robust algorithms able to change adaptively the sources and their weights/combination according to the dynamic environment. The objective is the implementation of a software platform for comparing the solutions for the integration among multiple sources and the integration in the tracking process according to the optimization principles identified by the theory.
- [Hardware] Realization of a demo for wireless transmission and sources management, constituted by two main parts: Software Defined Radio board to be installed on the UAV and a processing board for emulating the edge nodes on the ground. The objective is the experimental validation and comparison of the selected sub-optimal algorithms for the optimization problem in controlled but realistic scenarios.
Challenges  
  W.r.t. aerial systems at higher altitudes the fundamental challenges are:
  - UAVs traffic density with reduced distances, possibly frequent no-flight zones and presence of obstacles.
  - Propagation environment, for wireless communications, characterized by the presence of shadowing, multipath, sometimes absence of Line-of-Sight. The precision of any positioning technique, including the same GPS, is affected by the propagation conditions.
  - High data traffic, with possible impact on the use of 4G-5G mobile networks.
  - Selection and management of multiple sources with large number of variables and conditions. Positioning, with high performance requirements, is not solved by a single technology.
   
Research cooperation
The research activity will be done in cooperation with a team of Leonardo SpA and an international University.
   
Info
The Call for this industrial PhD is expected in July 2022. For additional information, please contact Luca Reggiani.
Information Transmission Group 
Dipartimento di Elettronica, Informazione e Bioingengeria (DEIB)  Politecnico di Milano 
P.zza Leonardo da Vinci 32, 20133 Milano - Italy 
e-mail: luca.reggiani@polimi.it 
Last updated May 2022