WP4-16

Enhanced Navigation Software

ID	WP4-16
Contributor	ACORDE
Levels	Platform, Function
Require	GLAD+ platform WP3-15_2
Provide	Navigation data (position, attitude, velocity)
Input	Raw sensed data from multi-constellation GNSS receivers, gyroscope and accelerometer data, barometer data
Output	Position, Attitude, Velocity
C4D building block
TRL	4
Parent Building block	WP3-15_2
Contact	fernando.herrera at acorde.com

This page describes the algorithmc improvements brought to GLAD+ by ACORDE in COMP4DRONES, taking as baseline, its outdoor geo-referenced position&attitude system GLAD+.

Description

In WP4 of COMP4DRONES, ACORDE has tackled the enhancement of the navigation software of its low-cost outdoor geo-referenced position and attitude estimation system GLAD+ WP3-15_2.

Following figure shows the main architecture of that soluion, i.e. a complex fusion algoritym which integrates raw data from several low-cost GNSS receivers, and from other low cost sensors (gyro, accelerometer, barometer). It consists of two main blocks, in turn, tightly interconnected:

• Tight Integration (TI) fusion block , to yield higher rate, but drift-free geo-referenced positioning data out from the multiconstellation GNSS receivers, and the low-cost sensors
• A Double Differences (DD) based attitude estimation (DDAtt) block able to estimate drift-free, accurate orientation (attitude) data, eventually fusioned with the drift affected orientation provided by the TI block.

Basic architecture of the multi-gnss fusion sensor functionality of GLAD+

One aspect of the navigation software enhancement tackled by ACORDE has been the exploitation of the novel low-cost receivers integrated in the HW platform developed in COMP4DRONES. The new receivers enable low-cost multi-constellation data, which need to be integrated and exploited in the navigation algorithm.

These receivers also enable specific reactive security features, an aspect also addressed in C4D and further explained in WP5-11_ACO.

Another aspect addressed in the context of WP4 is an analysis to assess if state-of-the-art deep learning methodologies might provide feasible and advantageous solutions for embedded targets. Specifically, the possibility to enhance a currently heuristic functionality integrated on the multi-baseline attitude estimation algorithm of GLAD+ was assessed.

Last, but not least, in the framework of WP4, ACORDE has also provided a "Mavlink interface" to ease SW, and therefore GLAD+ system integration.

Improvements

The following figures show GLAD+ position output (blue) vs RTK-postprocesed output (green) in one flight test performed in COMP4DRONES in a case where GLAD+ is configured to use only GPS, and in another case where GLAD+ is confiured to use multiconstellation (both GPS and Galileo).

• Accuracy improvement with Multi-Constellation (GPS-Galileo) in one flight test performed in COMP4DRONES
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  Only GPS

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  Multiconstellation (GPS-GAL)

Validation

The validation of the improved navigation software has been done by relying on raw data captured with the support of FADA-CATEC, drone integrator&operator partner in Use Case 2 of COMP4DRONES. For that, a former integration test (15/12/2020) was performed, where the multi-antenna setup (shown in the following figure), with the GLAD+ platform and a logger platform which allowed the capture of raw data was tested.

Multi-antenna set up checked 15/12/2020

After the integration test, ACORDE, with the support of CATEC, set up test flight for different fligth condtions, considering both, maneuvres that could challenge the positioning system, and feasible operations according CATEC experience (free flight). Those flights took place 2023/01/12.

• Some instants of the test flight
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  Drone used for the tests
  

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  Outdoor location of the tests
  

A set of raw catured data, including multi-constellation (GPS-Galileo) observables wehere captured, which served for test the algorithm and even for further refinementa and evaluation.