Nice job, dude! Now, what happens when you introduce stochastic variation (not just expectations)? Or if the swarm attacks in waves rather than a simultaneous burst? Also, how might degradation, sensor error, or mobility constraints shrink your effective kill capacity?
Gimme that sensitivity test! In practical use I’d love to see a sensitivity study or empirical fit of the model to actual test data. But even as a toy model, it moves the debate from intuition toward metrics.
The outcomes from the probability in your eqn will likely follow the binomial distribution so you will get times when you bring down more drones than you expect and others where you bring down less if any drones...
Nice job, dude! Now, what happens when you introduce stochastic variation (not just expectations)? Or if the swarm attacks in waves rather than a simultaneous burst? Also, how might degradation, sensor error, or mobility constraints shrink your effective kill capacity?
Gimme that sensitivity test! In practical use I’d love to see a sensitivity study or empirical fit of the model to actual test data. But even as a toy model, it moves the debate from intuition toward metrics.
The outcomes from the probability in your eqn will likely follow the binomial distribution so you will get times when you bring down more drones than you expect and others where you bring down less if any drones...
I like the framework. Having a quantifiable metric to look at for swarm defeat gives CDRs better tools to assess risk
Coach guns for all.
Thank you.
(Double barrel shotgun, short barrel, possibly very short gun with pistol grip).