Sensor data association for the Seawolf mid-life update (SWMLU) program

Christopher Dent; Duncan L. Hickman; Mark Bernhardt

doi:10.1117/12.541502

9 August 2004 Sensor data association for the Seawolf mid-life update (SWMLU) program

Christopher Dent, Duncan L. Hickman, Mark Bernhardt

Proceedings Volume 5429, Signal Processing, Sensor Fusion, and Target Recognition XIII; (2004) https://doi.org/10.1117/12.541502
Event: Defense and Security, 2004, Orlando, Florida, United States

Abstract

The Seawolf Mid-Life Update (SWMLU) programme is a major upgrade of the UK Royal Navy's principal point defence weapon system. The addition of an Electro-Optic sensor to the pre-existing 'I' and 'K' band radars presents a significant engineering challenge. The processing of the data from the 3 sensors into a fused picture such that a coherent view of which objects represent targets and own missiles is a key element of the overall system design and is critical to achieving the required system performance. Without this coherent view of the detected objects incorrect guidance commands will be issued to the Seawolf missiles resulting in a failure to successfully intercept the target. This paper reviews the sensor data association problem as it relates to the SWMLU system and outlines identified solution strategies. The SWMLU sensors provide complementary data that can be exploited through data association to maximise tracking accuracy as well as maintaining performance under sensor lost-lock conditions. The sensor data association approach utilises radar and EO properties from spatial and temporal domains. These characteristics are discussed in terms of their contribution to the SWMLU data association problem where it will be shown that the use of object attributes from the EO sensor and their behaviour over time is a critical performance factor.

Citation Download Citation

Christopher Dent, Duncan L. Hickman, and Mark Bernhardt "Sensor data association for the Seawolf mid-life update (SWMLU) program", Proc. SPIE 5429, Signal Processing, Sensor Fusion, and Target Recognition XIII, (9 August 2004); https://doi.org/10.1117/12.541502

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available