The radar cross section （RCS） changes rapidly with the variation of attitude angle during missile flight. Based on the relationship between the two， this paper proposed a missile target attitude angle inversion method using the particle swarm optimization （PSO） algorithm. The method estimated the target attitude angle by minimizing the mean square error between the observed RCS data and the RCS data derived from attitude angle inversion. Theoretical analysis shows that， under the premise that the target attitude angle does not change abruptly within a short time， the proposed method achieves a more accurate estimation of the target attitude angle. A series of simulation experiments was performed， and the results show that the proposed method can effectively invert the attitude angle sequence of the missile target.

Satellite navigation has undergone significant advancements in both military and civilian domains. Navigation warfare has emerged as a critical issue in contemporary localized military conflicts and great power rivalries. The urgent challenge lies in the rapid detection and localization of interference sources， providing actionable battlefield situational awareness for military command， enabling more adaptive decision-making processes， and ensuring the safety and reliability of navigational information. This paper introduces the concept of navigation warfare and provides an overview of passive positioning technology. It also analyzes commonly employed parameter estimation methods for passive positioning， compares observable， mathematical models， and positioning performance metrics associated with passive positioning techniques. Furthermore， it examines the current status and future trends in satellite navigation interference detection and location technologies.