SAR-based Augmented Integrity Navigation Architecture SARINA project - PDF document

See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/278254501 SAR-based Augmented Integrity Navigation Architecture SARINA project results presentation Conference Paper · January 2012 CITATIONS READS 2 269 10 authors , including: Mario Greco Stephane Querry Leonardo spa University of Strasbourg 32 PUBLICATIONS 189 CITATIONS 6 PUBLICATIONS 58 CITATIONS SEE PROFILE SEE PROFILE G. Pinelli Krzysztof Kulpa Ingegneria Dei Sistemi SpA, Italy Warsaw University of Technology 55 PUBLICATIONS 329 CITATIONS 359 PUBLICATIONS 2,534 CITATIONS SEE PROFILE SEE PROFILE Some of the authors of this publication are also working on these related projects: Detection and tracking of ground moving target View project Multitech SeCurity system for intercOnnected space control groUnd staTions-SCOUT project View project All content following this page was uploaded by G. Pinelli on 29 July 2015. The user has requested enhancement of the downloaded file.

SAR-based Augmented Integrity Navigation Architecture SARINA project results presentation M. Greco 1 , S. Querry 2,3 , G. Pinelli 1 , K. Kulpa 4 , P. Samczynski 4 , D. Gromek 4 , A. Gromek 4 , M. Malanowski 4 , B. Querry 2 , A. Bonsignore 1 , 1) IDS – Ingegneria Dei Sistemi – S.p.A. Pisa, Italy 2) PLV – Polyvionics, Paris, France 3) LSIIT – University of Strasbourg, Strasbourg, France 4) Institute of Electronic Systems Warsaw University of Technology Warszawa, Poland Abstract — This paper presents selected results obtain under this purpose, but the use of that sensor is limited by light SARINA project. SARINA is a SAR-based Augmented Integrity condition, fog and clouds. The day/night 24/7 operation can be Navigation Architecture proposed by authors of this paper. The assured by using microwave imaging based on SAR (Synthetic main goal of the SARINA project was designing and assessing a Aperture Radar). novel aircraft Inertial Navigation System (INS) for missile and This work was focused on building the mathematical UAV that will make use of features extracted from SAR/InSAR models and the simulations of navigation system augmented by imagery and on-board terrain landmark database in order to SAR vision. In the system navigation correction was based on ensure robustness against uncompensated IMU errors due to comparing the SAR images with image data base. possible GPS lack of. The SARINA (SAR-based augmented Integrity Navigation Keywords-SAR, Synthetic Aperture Radar, InSAR, Architecture) demonstrator was aimed to provide the feasibility Interfereometric SAR, SARINA, INS, Inertial Navigation System, study of novel navigation system for two kinds of unmanned IMU, Inertial Meassurement Unit. Platforms: Unmanned Aerial Vehicle (UAV) and Missile reaching TRL (Technological Readiness Level) 3 (out of 9) - I. I NTRODUCTION analytical and experimental critical function and/or The modern navigation systems comprise of inertial characteristic proof of concept. navigation unit and global Positioning System (GPS). The main goals of SARINA System Simulator was to Cooperation of both systems provides reliable and accurate evaluate the feasibility to retrieve aircraft state variables by navigation data required in many surface and airborne missions exploiting a novel INS based on novel Data Fusion Unit [2], [4], [6]. (DFU), able to deal with georeferencing inputs obtained by The problem arises when GPS data is not available either processing SAR and InSAR (Interferometric SAR) images [1], because of failure of GPS receiver of the denial action. In that [2]. case the navigation can be based in classical approach only on inertial data. The inertial systems error increase with time II. SARINA S YSTEM D ESCRIPTION (usually faster than square time function) and thus can be Two aerials platform were simulated within the project: reliable only for short missions. The chip navigation inertial systems build using integrated accelerometers can provide 1. MALE UAV: Predator B (empty: 2200kg; int.+ext. adequate accuracy only within several minutes, while very payloads: 1300+400kg; max. altitude: 7.5km, expensive optical systems can be used within several hours ra nge≈1000km, presented in Fig. 5 ) (depending on required accuracy). The common approach to 2. Cruise missile: Tomahawk (empty: 477kg; fuel+warhead increase navigation system accuracy is to provide payloads: 513+450kg; max. altitude: 6km, r ange≈1000km , position/velocity corrections based on the other sensors. For presented in Fig. 4) long time the optical sensors (e.g. TV cameras) were used for

The reference navigation sensor for SARINA simulator was a Navigation Grade Inertial Measurement Unit (IMU): LN- 100G from Northrop Grumman (Accuracy 0.05°, 9 .8kg, 28x18x18cm 3 ) presented in Fig. 2. The reference SAR Sensor for SARINA Simulator was Pico SAR (stripmap, range>20km, 1m resolution, 10kg, 32x23x16cm 3 ), presented in Fig. 1. The reference Air Data Computer (ADC) Sensor model implemented inside the SARINA Simulator has been: The Figure 4. An example of reference missile platform used for SARINA 2018R from the Goodrich Company (Pressure altitude simulator (Tomahawk missile produced by Hughes (presently part of Raytheon [9]) accuracy around 7 feet), presented in Fig. 3. Figure 1. An example of reference SAR sensor used for SARINA simulator (Pico SAR system produced Selex Galileo [7]) Figure 5. An example of reference UAV platform used for SARINA simulator (Predator UAV produced by General Atomics Aeronautical [10]) III. R ESULTS E XEMPLIFICATIONS The main aim of the simulation was to show the accuracy improvement during the mission, when GPS data is not available. The sample result of exploiting SAR data during UAV – MISSION is presented in Fig 6, where S is Starting Point, WP – Way Point (every WP corresponds to either SAR or InSAR image acquisition), E – End Point. The figure clearly shows the expected differences among planned trajectory, Figure 2. An example of reference IMU platform used for SARINA trajectory based on SARINA system and trajectory based on a simulator (LN-100G system produced Northrop Grumman [8]) traditional INS. Note that both the simulations (SARINA and the traditional INS) assume a jammed GPS. However, only the SARINA system would be robust against any drift caused by uncompensated IMU (due to the jammed GPS) as opposed to the traditional INS, which shows a dramatic drift. Figure 3. An example of reference ADC sensor used for SARINA simulator (2018R (produced by Goodrich [9])

extracted radar coordinates (those obtained under the actual SAR viewing geometry) and the world coordinates (those in the mission Data Base - DB) of the same Landmark (e.g. the biggest building) are used to retrieve the aircraft state variables. 0 500 1000 Figure 6. Example of UAV trajectories (S – starting point; WP – waypoint; E – end point): planned trajectory, trajectory based on SARINA system (jammed GPS), trajectory based on a traditional INS (jammed GPS). 1500 8800 9000 9200 9400 9600 9800 10000 10200 10400 10600 The details of SAR mission concept is presented in Fig 7. The mission was fulfilled in the suburban scenario. The Landmarks (a) available in SAR image, was acquired on-board and compared 0 with the data based stored in computer memory. The drift correction was based on the best match between planned (latitude/longitude./altitude) and automatically extracted (azimuth/slant-range) Landmark coordinates as a function of 500 aircraft state variables. 1000 1500 8800 9000 9200 9400 9600 9800 10000 10200 10400 10600 (b) Figure 8. Suburban Scenario: (a) SAR image (x-axis – slant range; y-axis – cross-range) simulated according to the available telemetry data; (b) result of the ATR chain, which recognizes two planned buildings and four cross-roads. The SAR concept is designed to be successful in urban and suburban scenario, however in open lands (e.g. in mountains) there are more difficulties to find very characteristic Figure 7. Suburban Scenario: Landmarks available in SAR image, acquired on-board (SAR image: courtesi of Agenzia Spaziale Italiana – ASI in the landmarks, so instead of SAR image comparison the hight framework of “Accordo Quadro Cooperazione”) profiles obtained by InSAR technique was tested. Fig. 9 presents InSAR mission concept using DTM data base. The The automatic extraction step is performed by a novel mission was simulated in Alpine scenario and no landmarks Automatic Target Recognition chain, which is able to were available in InSAR images, acquired on-board. The automatically extract the planned mission Landmarks [2], [3]. correction algorithm was as follows: Fig 8 presents an exemplification of suburban Scenario,  For every WayPoint (WP), Phase Field (PF) is overlapped where: (a) SAR image (x-axis – slant range; y-axis – cross- to the local orography. range) is simulated according to the available telemetry data  Drift correction based on the best match between planned and the expected Landmarks [14]; (b) the ATR chain (based on the expected Digital Terrain Model - DTM) and recognizes two planned buildings and four cross-roads (i.e. the automatically extracted PFs as a function of aircraft state six planned Landmarks), by resorting not only to their variables. expected geometrical features (e.g. length, width, height), but also to their expected position in the SAR image. Finally, both