GPS Delay Spoofing Compensation by Mitigating Tracking Error Based on Neural Networks

In recent years, spoofing is known as a perceived emerging threat to GPS receivers. The spoofing attack result is large navigational solution errors in the unsuspecting user with potentially serious consequences. Since the spoofing signal imitates the authentic one, the receiver cannot detect the presence of that. Therefore, detection and mitigation of spoofing is more difficult than other interferences. In this paper, we try to study all of proposed anti-spoofing approaches for single frequency GPS receivers. At first the general process of each technique is described summarily, then its challenges, advantages and disadvantages are pointed. Finally, a novel and applicable idea based on Neural Network (NN) is introduced for spoofing compensation. In that we use a back propagation algorithm in range domain for estimation and compensation of tracking code and carrier error due to spoofing attack. In this way, by utilizing NNs we can mitigate spoofing error with an average of 82% and a tolerance of 2%.