Big Bang Big Crunch based Near-Optimal Guidance Law for Interceptor Problem

This paper proposes a time-energy near-optimal guidance law for missile-target engagement scenarios. The guidance law uses a nature inspired meta-heuristic optimization algorithm. The classical pure proportional navigation (PPN) guidance law is augmented with a polynomial function of heading error and the parameters of this guidance law are optimally tuned using Big-Bang Big-Crunch (BBBC) algorithm. The pro-posed BBBC tuned all aspect proportional navigation (BBBCPN) guidance law tackles the primary requirement of interception of the target and is also time-energy efficient. Along with initial high heading error, a constraint on the lateral acceleration of the missile is also considered. These two conditions are included to make the guidance problem more realistic and challenging. The proposed guidance law is compared with other standard guidance laws which establishes its effectiveness.