Potential of Multi constellation Global Navigation Satellite System in Indian Missile Test Range Applications

In this paper, the potentials of using Global Navigation Satellite System (GNSS) techniques in the complex calibration procedure of the tracking sensors for missile test range applications have been presented. The frequently used tracking sensors in test range applications are- electro-optical tracking stations (EOTS) and tracking radars. Over the years, the EOTS are used as the reference for bias estimation of the radars. With the introduction of GPS in test range applications, especially the DGPS, the reference for bias estimation got shifted to DGPS from the EOTS. However, the achievable position solution accuracy is limited to the order of a few meters for DGPS, EOTS, and Radars. With the evolution of Multi-constellation GNSS and carrier-phase based measurement techniques in satellite navigation, achievable position solution accuracies may be improved to sub-meter level. New navigation techniques like real time kinematic (RTK) and precise point positioning have the potentials for use in the calibration procedures of the missile test ranges to the accuracies of centimeter-level. Moreover, because of the availability of a large number of navigation signals over the Indian region, multi-constellation GNSS receivers can enhance signal availability, reliability, and accuracies during the calibration of missile test ranges. Currently available compact, low-cost GNSS modules also offer the possibilities of using these for cost-effective, networked RTK for dynamic calibration of test ranges reducing cost and resource requirements

Partially observable semi-markov games with discounted payoff

We study partially observable semi-Markov game with discounted payoff on a Borel state space. We study both zero sum and nonzero sum games. We establish saddle point equilibrium and Nash equilibrium for zero sum and nonzero sum cases, respectively

Risk minimizing option pricing in a semi-Markov modulated market

We address risk minimizing option pricing in a semi-Markov modulated market where the floating interest rate depends on a finite state semi-Markov process. The growth rate and the volatility of the stock also depend on the semi-Markov process. Using the Föllmer-Schweizer decomposition we find the locally risk minimizing price for European options and the corresponding hedging strategy. We develop suitable numerical methods for computing option prices

Risk Minimizing Option Pricing in a Semi-Markov Modulated Market

We address risk minimizing option pricing in a semi-Markov modulated market where the floating interest rate depends on a finite state semi-Markov process. The growth rate and the volatility of the stock also depend on the semi-Markov process. Using the Föllmer–Schweizer decomposition we find the locally risk minimizing price for European options and the corresponding hedging strategy. We develop suitable numerical methods for computing option prices

Partially observable semi-Markov games with discounted payoff

We study partially observable semi-Markov game with discounted payoff on a Borel state space. We study both zero sum and nonzero sum games. We establish saddle point equilibrium and Nash equilibrium for zero sum and nonzero sum cases, respectively

Semi-Markov decision processes with partial observation

We study a semi-Markov decision process on a Borel state space where the state of the system is not known to the decision maker but it takes decisions based on an observation process. We transform this into an equivalent problem with complete information. We then establish the existence of optimal policies

Portfolio Optimization in a Semi-Markov Modulated Market

We address a portfolio optimization problem in a semi-Markov modulated market. We study both the terminal expected utility optimization on finite time horizon and the risk-sensitive portfolio optimization on finite and infinite time horizon. We obtain optimal portfolios in relevant cases. A numerical procedure is also developed to compute the optimal expected terminal utility for finite horizon problem

Risk Minimizing Option Pricing for a Class of Exotic Options in a Markov-Modulated Market

We address risk minimizing option pricing in a regime switching market where the floating interest rate depends on a finite state Markov process. The growth rate and the volatility of the stock also depend on the Markov process. Using the minimal martingale measure, we show that the locally risk minimizing prices for certain exotic options satisfy a system of Black-Scholes partial differential equations with appropriate boundary conditions. We find the corresponding hedging strategies and the residual risk. We develop suitable numerical methods to compute option prices

Digital healthcare: The only solution for better healthcare during COVID-19 pandemic?

The huge impact of the COVID-19 pandemic on global healthcare systems has prompted search for novel tools to stem the tide. Attention has turned to the digital health community to provide possible health solutions in this time of unprecedented medical crisis to mitigate the impact of this pandemic. The paper shall focus on how digital solutions can impact healthcare during this pandemic