Improving Structural Power Content Analysis Robustness for Satellite Navigation Applications

Many critical applications exhibit a growing dependency on Global Navigation Satellite Systems (GNSS), which has led to GNSS jamming and spoofing becoming an increasing threat to society. The Structural Power Content Analysis (SPCA) algorithm is a pre-despreading, low-complexity, and effective method to detect spoofing events, but in practice it is seen that false alarms are being generated in certain jamming scenarios. To mitigate these effects, alternative filtering techniques are evaluated and tested on both simulated data and publicly available spoofing datasets. Effective false alarm reduction with only a minor degradation in spoofing detection sensitivity is demonstrated.

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Published
2025-04-14
DOI
https://doi.org/10.3390/engproc2025088034
Primary Topic
Technology and Data Analysis
Type
article
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article

Improving Structural Power Content Analysis Robustness for Satellite Navigation Applications

J.E. Rijnsdorp, André Young
Technology and Data Analysis
article

Improving Structural Power Content Analysis Robustness for Satellite Navigation Applications

J.E. Rijnsdorp, André Young
article en

Abstract

Many critical applications exhibit a growing dependency on Global Navigation Satellite Systems (GNSS), which has led to GNSS jamming and spoofing becoming an increasing threat to society. The Structural Power Content Analysis (SPCA) algorithm is a pre-despreading, low-complexity, and effective method to detect spoofing events, but in practice it is seen that false alarms are being generated in certain jamming scenarios. To mitigate these effects, alternative filtering techniques are evaluated and tested on both simulated data and publicly available spoofing datasets. Effective false alarm reduction with only a minor degradation in spoofing detection sensitivity is demonstrated.

Science and Technology Corporation (Netherlands) (NL)
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