Performance Prediction of Directed Energy Weapons

Abstract

Directed energy weapons provide a number of useful functions for the modern fighting force, and hence it is useful to produce a framework in which such a weapon's performance can be predicted. Towards this objective this paper introduces a new stochastic model to determine the number of targets defeated by a directed energy weapon over a given time interval. The key to this is to introduce a general queueing model, where arrivals are modelled by a renewal process, and the service time of a target being affected by the weapon is related to its probability of defeat. The queue is assumed to have an infinite capacity, and it is shown how the waiting time of detected threats can be modelled by an auxiliary delay process. A random variable counting the number of targets processed by the queue is then defined. Several functions constructed from this random variable will be investigated in order to identify a suitable metric for assessing performance. In order to facilitate this an example where a high energy laser is used for threat defeat is examined to investigate the utility of the identified performance metrics. As will become apparent, the modelling framework has considerable utility due to the fact that it can be used for performance prediction of any weapon system where an arrival process of threats and corresponding probability of defeat can be specified.

Drones are Endangering Energy Critical Infrastructure, and How We Can Deal with This

“…Thus, allowing the weapon to take out drones before they cause damage to the grid. This technology can also have very large effective ranges of around 20 km [36,37], so not many of these devices would need to be used to protect large expanses of transmission lines. However, this would be an expensive undertaking to set up on the scale of the grid.…”

Swarm UAV Defeat Modelling through Lifetime Distribution Analysis

“…It will be assumed that there is a fixed number of threats N and that the swarm is visible to the HPRF DEW at time t = 0. Additionally, it will be supposed that members of the swarm, although spatially distributed, travel at the same speed toward the HPRF DEW; otherwise, the swarm problem may be examined as a single UAV defeat study, as in the approach of [12].…”

Guarantees of Minimum Performance Levels With Directed Energy Weapons

“…Hence the distance to the target at time t is R j (t) = max{0, ν j (T j −t)}. The DEWs are assumed to operate in the same setting as applied in [13,19], whose models for propagation have been based upon that in [20]. The key operational parameters are that all DEWs operate at a wavelength of λ = 1.045 × 10 −6 metres, with a power level P j Watts and duty cycle C j .…”

“…The DEW dwell time on the target is modelled by a truncated exponential distribution with parameter µ τ seconds and that the target has an average illumination area parameter µ σ square metres. As in [13] it will be assumed that µ τ = 1/3 seconds and µ σ = ((1.045 2 )/9) × 10 −8 µ r , where µ r is the radar cross section (RCS) of the target in square metres.…”

“…Given the utility of DEWs for defeating airborne threats there has been much interest in the performance prediction of DEWs, and in particular, the case where a degree of collaboration between defensive platforms is utilised. Recent work at Defence Science and Technology Group (DSTG) has not only examined the performance analysis of single DEW effectors [13], but has explored their application to active protection systems (APS). An APS permits a series of armoured fighting vehicles (AFVs) to be equipped with an automatic threat detection and defeat system [14,15].…”