Received signal strength-based emitter geolocation using an iterative maximum likelihood approach

Batch-mode maximum likelihood (ML) received signal strength (RSS) emitter geolocation algorithms produce location estimates from a block of data collected over an observation period using either a single sensor or collected at one time instant by multiple spatially dispersed sensors. Due to practical constraints such as processor speed, memory for data storage, time for data transfer and communications bandwidth, batch-mode algorithms can only be implemented in real-time for small data sets. This paper presents an iterative formulation of the likelihood function for the ML RSS geolocation algorithm for real-time implementation with large data sets. Simulation and experimental results are included to validate the proposed formulation