Consultants from the Defence Science and Know-how Laboratory (Dstl) have performed a key function in supporting the Military Warfighting Experiment Maintain and Shield train at His Majesty’s Naval Base Portsmouth. Dstl scientists from a variety of specialisms together with sensing, platform survivability, human science, autonomy and energy deployed to function and assess quite a lot of applied sciences corresponding to novel robotics and information fusion. The aim of Military Warfighting Experiment (AWE) Maintain and Shield is to determine present, rising and novel applied sciences from trade companions to tell present and future tools programmes and encourage nearer collaboration throughout authorities, allies, companions and trade to make the Military extra deadly, agile, resilient and chronic.

AWE will get these applied sciences into the palms of the consumer and supplies the chance to develop enough proof to:
de-risk main idea and tools programmes – by figuring out and assessing candidate programs, informing future necessities and funding selections
improve relationships with trade, companions and allies – by engagement, cooperation and burden-sharing the place applicable
speed up Military transformation – by focussed hypotheses, integrating associated know-how and additional exploiting by spiral improvement and idea functionality demonstrators


The Portsmouth train is a part of the second part within the AWE City collection which focuses on how the Military can maintain and defend a Brigade (and under) drive within the city setting by the utilisation of clever logistics, novel medical extraction and autonomous car extraction. It additionally goals to evaluate the implementation of bodily and non-physical limitations which embody counter-uncrewed air programs (C-UAS) and counter-cyber and electromagnetic actions (C-CEMA) to make sure automated platforms are survivable on the fashionable battlefield from round 2030. Dstl specialists had been concerned within the down number of the 159 programs initially submitted by trade towards Military Warfighting Experiment Maintain and Shield particular hypotheses.

The train noticed navy troops testing using novel trade applied sciences. (UK MOD/ Crown copyright)

Lt Col Arthur Dawe, Commanding Officer, Infantry Trials and Improvement Unit, stated:”Dstl is continually looking for to enhance the effectiveness of the UK’s armed forces by figuring out and assessing novel applied sciences. These new applied sciences will supply operational benefit in a lot of areas, corresponding to improved sensing to determine and monitor adversaries, or by rising the pace and compatibility of knowledge, enabling commanders to make sooner and extra impactful selections.”

All through the method greater than 20 Dstl employees labored carefully to assist QinetiQ, DE&S and Military Trials and Improvement models (TDUs) of their assessments of programs. In the end, roughly 20 applied sciences progressed to the ultimate stage, the built-in experimentation evaluation, at Portsmouth Naval Base in November 2022. On this simulated reside fireplace occasion, troops from 2 YORKS and three PARA, in addition to allied companions from parts of the Dutch Military’s Robotics and Autonomous Methods Unit and the US Military Experimentation Drive used the trade applied sciences in consultant platoon stage force-on-force city eventualities.

Employees noticed using these applied sciences within the actions, offering suggestions to navy suppliers and AWE organisers, serving to information the event of future capabilities for Military use in for city operations. Dstl helps trials and experimentation for the entire armed forces together with multi-national train corresponding to Challenge Convergence and the Contested City Surroundings. Challenge Convergence 2022 (PC22) has concerned a number of thousand US, UK and Australian members of the Armed Forces, together with round 500 British Military personnel. Scientists at Dstl have led a novel city navy experiment, often known as the Contested City Surroundings(CUE) train .