Robust Target Localization Based on Squared Range Iterative Reweighted Least Squares

Alireza Zaeemzadeh, Mohsen Joneidi, Behzad Shahrasbi & Nazanin Rahnavard
In this paper, the problem of target localization in the presence of outlying sensors is tackled. This problem is important in practice because in many real-world applications the sensors might report irrelevant data unintentionally or maliciously. We propose a localization method based on robust statistics, seeking to eliminate the effect of outliers. The main goal is to achieve optimal or near-optimal performance for different outlier types and different contamination ratios. The problem is formulated by...
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