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EADS - DOD Collaboration on MILDS MW

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Presentation on theme: "EADS - DOD Collaboration on MILDS MW"— Presentation transcript:

1 EADS - DOD Collaboration on MILDS MW
EADS Defence Electronics & DSTO Presentation 13.April.2010 AOC Adelaide Proprietary information: This document contains EADS Germany GmbH (EADS) proprietary and company confidential information. It may not be reproduced in whole or in part without the written consent of EADS and must not be disclosed to persons not having need for such disclosures. The contents of this document may not be disclosed to third parties without the express written permission by EADS. Violations will lead to indemnification claims. All rights in respect of patents property or other industrial property rights reserved.

2 History

3 Introduction of AAR-60 within the ADF
MWS ? ECHIDNA Contract MILDS selected for Echidna Project (AIR 5416, Phase 2A) Initially contracted by CoA for Blackhawk & CH-47 under ECHIDNA as part of full EWSP suite..but then standalone “HeSA” suite (including MCDU, INU) contracted for “interim” solutions which have since been retained. Also contracted for P3C in HeSA configuration under AIR5276, Phase 4

4 MILDS HeSA Equipment

5 CH-47

6 AP-3C

7 In total about 100 ADF aircraft are equipped with MILDS
ARH Tiger, MRH90 MILDS is also on board of ARH Tiger and MRH90 helicopters as part of the standard EWSP suite In total about 100 ADF aircraft are equipped with MILDS

8 Collaboration between DoD and EADS

9 Background of Collaboration
Because MILDS is considered crucial for A/C protection against SAMs, DSTO was tasked to assess performance against specific threats DSTO analyzed data recordings from live missile firings From operational missions in theater After intensive discussions both ADF and EADS came to the conclusion that There is potential for performance improvement of MILDS performance against specific threats The parties would collaborate in undertaking algorithmic adaptations ( via new SW updates)

10 IMAGE PROCESSING “THREATS” Marginal tracks from/ to other sensors
Prioritized tracks from/ other sensors Tracking Object- classification Fusion of data from all sensor heads Established tracks Prioritized tracks Detected objects INS data Object- segmentation "Pre-processing" Communication “THREATS” Images 1 1 1 1 1

11 Collaboration Collaboration Model Operational Data Recordings
OPS Feedback Tools MILDS SW 3.x

12 Collaboration Results
Result of 1.5 years of common work is SW version 3.x of MILDS Increased declaration performance ( new missile types ) Lower FAR in specific environments ( e.g. Afghanistan, Iraq ) Special adaptation for ADF needs Benefits for other MILDS customers Improved MILDS performance Operational Feedback ( combat experience ) Independent Reference Customer Clear Win – Win Situation for all parties

13 Leasons Learned from such Collaboration
Win – Win Arrangement for all parties and all customers benefit ADF is a excellent partner for such arrangements EADS able to share know-how without fear of IP leakage Improved AAR-60

14 Collaboration between DoD & EADS on MILDS MW
Introduction of Hostile Fire Indication (HFI)

15 Aim of current Collaboration
Introduction of new functionality into MILDS Block II sensor using more advanced MILDS-F internals Based on requirements from ADF Work-share for HFI solution Small arms fire focus  DSTO RPG focus  EADS

16 HFI with MILDS – DSTO perspective Introduction
MILDS Block 2 has ability to detect Hostile Fire At useful ranges Against various calibres Can detect muzzle flash, tracer, RPG emissions Opportunity for HFI inside current architecture of MILDS Block 2 Different objects to track mean extra information needed for HFI algorithm Additional preprocessor outputs Additional main processor software

17 HFI with MILDS – DSTO perspective What are the problems in HFI?
Detect and track tracer Passive measurements on platform Track along as much of tracer flight Locate origin of small arms fire Bearing to weapon Geolocation of weapon World coordinates viewpoint HFI algorithm performance must not affect MAWS algorithm performance First problem is tracking the tracer rounds Second problem is using the tracks to give position of shooter: initially bearing, then geolocation over time (triangulation)

18 HFI with MILDS – DSTO perspective Data collection and testing
Clutter Flight Trials Targeting Rotary Platform 5x MILDS-F Sensors IR Sensors Visible Sensors Developing DAQ HW – synchronised recordings Live Fire Trials Capture representative engagement geometries Approximate operational rotary-wing sensor geometry Testing current algorithm state Algorithm improvement Simulation validation Data gathering and testing. DAQ HW = digital acquisition hardware Should we

19 HFI with MILDS – DSTO perspective End point
Desired end point is tested algorithm that can be transitioned to engineering into MILDS Block II More complete threat warning solution for ADF Upgrade to HFI capability will require sensor replacement only

20 AMPS-MV Helicopter RPG protection

21 AMPS-MV System Aproach
Detection of RPG ejection by AAR-60 Confirmation by Active Confirmation Sensor Active PD a small beam ( few degree ) Adjustable antenna using precision info from AAR-60 Confirmation of RPG Measurement of distance and velocity Activation of countermeasure at precise distance

22 Questions?

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