Visual Passive Ranging Method Based on Re-entrant Coaxial Optical Path and Experimental Verification

To overcome the shortcomings of the traditional passive ranging technology based on image, such as poor ranging accuracy, low reliability and complex system, a new visual passive ranging method based on re-entrant coaxial optical path is presented. The target image is obtained using double cameras with coaxial optical path. Since there is imaging optical path difference between the cameras, the images are different. In comparison of the image differences, the target range could be reversed. The principle of the ranging method and the ranging model are described. The relationship among parameters in the ranging process is analyzed quantitatively. Meanwhile,the system composition and technical realization scheme are also presented. Also, the principle of the method is verified by the equivalent experiment. The experimental results show that the design scheme is correct and feasible with good robustness. Generally, the ranging error is less than 10% with good convergence. The optical path is designed in a re-entrant mode to reduce the volume and weight of the system. Through the coaxial design,the visual passive range of the targets with any posture can be obtained in real time. The system can be widely used in electro-optical countermeasure and concealed photoelectric detection.

High-Risk LEO Satellite Network Path Detection Based on Spatial and Temporal Delay Anomaly Analysis

The gradual deployment of Low-Earth Orbit(LEO)mega constellations with inter-satellite links(ISLs)promises ubiquitous,low-latency,and high-throughput satellite network services.However,networked LEO satellites with ISLs are also at risk of routing attacks such as hijacking.Existing defenses against route hijacking in terrestrial networks can hardly work for the LEO satellite network due to its high spatiotemporal dynamics.To deal with it,we propose RPD,a high-risk routing path detection method for LEO mega-constellation networks.RPD detects abnormal high-risk LEO network paths by checking the consistency between the path delay and the geographical distance.This is efficiently achieved by combining in-band measurements and out-of-band statistical processing to detect the anomaly of the clustering feature in the reference delay matrix.RPD avoids the recalculation of the header cryptographic marks when the handover occurs,thus greatly reducing the cost and improving the performance of highrisk path detection.Experiments showed that the proposed RPD mechanism achieves an average detection accuracy of 91.64%under normal network conditions,and maintain about 89%even when congestion occurs in multiple areas of the network and measurement noise is considered.In addition,RPD does not require any cryptographic operation on the intermediate node,only minimal communication cost with excellent scalability and deployability.