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A passive location method based on energy-based fast regression algorithm for multi-node systems

agents-and-multi-agent-systems
algorithms-and-analysis-of-algorithms
data-mining-and-machine-learning

Abstract

To tackle the high computational complexity and poor real-time performance of passive localization in complex electromagnetic environments, this paper proposes a multi-node cooperative localization method using an Energy-based Fast Regression Algorithm (EFRA). Conventional localization methods based on the Received Signal Strength Indicator (RSSI) require iterative solutions to nonlinear optimization problems, which are computationally expensive. By theoretically deriving a variable substitution, we transform the nonlinear Friis transmission equation into a linear regression model of node coordinates, converting the localization problem into a linear least-squares problem that can be solved directly without iteration. The theoretical lower bound of localization accuracy under different node geometries is analyzed, revealing the relationship between accuracy, distance, node spacing, and layout. Simulations demonstrate that the proposed algorithm achieves accuracy comparable to Maximum Likelihood Estimation (MLE) while reducing computational complexity to a linear level. This method is especially suitable for high-real-time applications such as electronic warfare and emergency communications.
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