Global Navigation Satellite System Spoofing Research Articles

GNSS Radio Frequency Interference Monitoring from LEO Satellites: An In-Laboratory Prototype.

The disruptive effect of radio frequency interference (RFI) on global navigation satellite system (GNSS) signals is well known, and in the last four decades, many have been investigated as countermeasures. Recently, low-Earth orbit (LEO) satellites have been looked at as a good opportunity for GNSS RFI monitoring, and the last five years have seen the proliferation of many commercial and academic initiatives. In this context, this paper proposes a new spaceborne system to detect, classify, and localize terrestrial GNSS RFI signals, particularly jamming and spoofing, for civil use. This paper presents the implementation of the RFI detection software module to be hosted on a nanosatellite. The whole development work is described, including the selection of both the target platform and the algorithms, the implementation, the detection performance evaluation, and the computational load analysis. Two are the implemented RFI detectors: the chi-square goodness-of-fit (GoF) algorithm for non-GNSS-like interference, e.g., chirp jamming, and the snapshot acquisition for GNSS-like interference, e.g., spoofing. Preliminary testing results in the presence of jamming and spoofing signals reveal promising detection capability in terms of sensitivity and highlight room to optimize the computational load, particularly for the snapshot-acquisition-based RFI detector.

Global Navigation Satellite System Spoofing Detection in Inertial Satellite Navigation Systems

The susceptibility of global navigation satellite systems (GNSSs) to interference significantly limits the possibility of their use. From the standpoint of possible consequences, the most dangerous interference is the so-called spoofing. Simultaneously, in most cases of GNSS use, an inertial navigation system (INS) or an attitude and heading reference system (AHRS) is also present on the board of mobile objects. In this regard, the research goal is to assess the possibility of detecting GNSS spoofing in inertial satellite navigation systems. This paper examines the method for detecting GNSS spoofing by combining a pair of commercially available GNSS receivers and antennas with an INS or AHRS. The method is based on a comparison of the double differences of GNSS carrier phase measurements performed by receivers under conditions of resolved integer ambiguity and the values of the range double differences predicted using an INS. GNSS carrier phase integer ambiguity can be resolved using a strapdown inertial navigation system (SINS) or AHRS data. The mathematical model of GNSS phase difference measurements and the SINS-predicted satellite range differences model are given. The proposed algorithm calculates the moving average of the residuals between the SINS-predicted satellite range double differences and the measured GNSS carrier phase double differences. The primary criterion for spoofing detection is the specified threshold excess of the moving average of the double difference residuals. Experimental studies are performed using simulation and hardware-in-the-loop simulation. The experimental results allow us to evaluate the efficiency of the proposed approach and estimate the potential characteristics of the spoofing detection algorithm based on it.

A GNSS Spoofing Detection and Direction-Finding Method Based on Low-Cost Commercial Board Components

The Global Navigation Satellite System (GNSS) is vulnerable to deliberate spoofing signal attacks. Once the user wrongly locks on the spoofing signal, the wrong position, velocity, and time (PVT) information will be calculated, which will harm the user. GNSS spoofing signals are difficult to carry out spoofing attacks in the direction of arrival (DOA) of the real signal, so the spoofing detection method based on DOA is very effective. On the basis of identifying spoofing signals, accurate DOA information of the signal can be further used to locate the spoofer. At present, the existing DOA monitoring methods for spoofing signals are mainly based on dedicated antenna arrays and receivers, which are costly and difficult to upgrade and are not conducive to large-scale deployment, upgrade, and maintenance. This paper proposes a spoofing detection and direction-finding method based on a low-cost commercial GNSS board component (including an antenna). Based on the traditional principle of using a multi-antenna carrier phase to solve DOA, this paper innovatively solves the following problems: the poor direction-finding accuracy caused by the unstable phase center of low-cost commercial antennas, the low success rate of spoofing detection in a multipath environment, and the inconsistent sampling time among multiple low-cost commercial GNSS boards. Moreover, the corresponding prototype equipment for spoofing detection and direction-finding is developed. The measured results show that it can effectively detect spoofing signals in open environments. Under a certain false alarm rate, the detection success rate can reach 100%, and the typical direction-finding accuracy can reach 5°.

Optimal decision for the satellite navigation system under navigation countermeasures based on spoofing effect evaluation results

AbstractThis paper realizes the evaluation and optimal decision of the spoofing effect on the global navigation satellite system (GNSS) under navigation countermeasures based on the game perspective, to overcome the limitations of current relevant research findings and maintain the secure application of the GNSS and maximize its defensive benefit during countering. An evaluation system based on the perspective of the game between spoofing strategies and defense measures is created to build the benefit matrix, which can solve the limitation in building a benefit matrix (the vital element in a game) that conforms to the confrontation‐oriented GNSS spoofing properties. Based on the built benefit matrix, a method integrating the grey expert‐based system with the hybrid evolutionary method is developed to realize quantifying the matrix and further make the optimal decision stably, which can solve the uncertainties of qualitative indices during quantifying and no global optimal solution for benefit equations deduced from the quantified matrix. Finally, based on various judgment principles, simulation and testing results verify the effectiveness of the obtained results and the superiority of the proposed method by comparing the results solved by the method in this paper with the results obtained by other decision‐making processing methods.

Preparations for Galileo PRS in Poland.

This article discusses the increasing security risk for the Global Navigation Satellite System (GNSS) due to both unintentional and deliberate interference (attacks), which have gotten significantly worse in 2022 due to tense the international situation. The upcoming Galileo Public Regulated Service (PRS), which is more resilient and robust than initial GNSS open services, is one of the key solutions for that problem. The technical description of this service, aspects regarding its implementation in the EU and the role of designated governmental authorities in that process are extensively covered in the first sections of the article. The next relevant issue brought up in the paper is the PRS signals' coexistence with amateur services operating within the same frequency resources, which have recently became a source of significant controversy in Europe. Finally, the article presents the Polish contribution to the Galileo PRS preparatory actions, covering the participation in two international R&D projects, the developed measurement station and initial results for the GNSS receiver's jamming and spoofing resistance tests, as well as the concept of the Galileo PRS threats detection system.

A GNSS Instrumentation Covert Directional Spoofing Algorithm for UAV Equipped With Tightly-Coupled GNSS/IMU

Measurement and navigation users cannot operate without the positioning, navigation, and timing (PNT) service provided by the global navigation satellite system (GNSS) instrumentation, but users are also faced with unpredictable and complex interference and even spoofing. In order to effectively control and even counter the unmanned aerial vehicle (UAV) that may pose security threats, using the GNSS spoofing technology to counter UAV is an effective and important technical means. Compared with the existing spoofing algorithms, this article fully considers the navigation system configuration and flight control principle, as well as antispoofing module of UAV equipped, the UAV dynamic model under GNSS spoofing environment is established, and the response law of UAV state to spoofing is analyzed. In order to realize the covert directional spoofing on UAV equipped with tightly-coupled GNSS and inertial measurement unit (IMU), a GNSS covert spoofing algorithm is proposed. The algorithm includes a fixed-point four-step spoofing strategy and pays attention to avoiding the least-squares residual receiver autonomous integrity monitoring (LSR-RAIM) of UAV, so as to ensure the concealment of the deception process. Through the construction of experimental platform and experimental analysis, the effectiveness and concealment of the algorithm are verified. The experiment shows that the spoofing yaw angle error of GNSS covert directional spoofing is −0.03°. In addition, the spoofer has effectively avoided the LSR-RAIM of UAV system in the whole process, and the evasion rate has reached 100% to achieve covert spoofing. For the actual spoofing scenario application, the spoofing yaw angle error can meet the actual needs. Future work will focus on the research and design of more complex covert spoofing algorithms to meet the spoofing needs of UAV equipped with more complex navigation systems and antispoofing techniques.

Evolution of Timing Services From 5G-A Toward 6G

5G-Advanced and 6G networks will serve as critical infrastructure for society and will enable a new generation of immersive use cases, such as the metaverse, wherever people roam. Absolute time is an essential component to ensure critical use cases, synchronize media playout, and timestamp events to be used in machine learned contexts. Until now, timing on the go has mainly been acquired by satellite, e.g., Global Navigation Satellite System (GNSS), but a terrestrial timing solution using cellular networks is required to extend coverage to deep indoors and to offer resilient operation in GNSS-denied environments (e.g., due to GNSS signal interference, jamming and spoofing). In this paper, we detail the use cases for timing to be provisioned by 5G-Advanced and 6G networks. Then, we discuss the architectural enablers for timing as a service in current 5G and 5G-Advanced standard and timing resiliency enablers under discussion in the 3rd Generation Partnership Project (3GPP). Finally, we discuss the gaps and research challenges to be solved in 6G for future-proof timing solutions.

Selection of Areas for Effective GNSS Spoofing Attacks to a Vehicle-mounted MSF System based on Scenario Classification Models

The inherent vulnerability of the Global Navigation Satellite System (GNSS) leads to the ease of implementation of spoofing attacks. The latest GNSS spoofing attack schemes still suffer from low success rate, long attack time, and poor concealment. To improve the success rate, an efficient GNSS spoofing attack method for a vehicle-mounted Multi Sensors Fusion (MSF) system is proposed based on the scenario classification models with a spatial database. Firstly, the influence of the two typical urban scenarios, which are 1) the road with buildings on both sides and 2) tunnels, on the GNSS spoofing attack is analyzed. Then a dynamic Bayesian network model considering the sky visibility generated with the 3D building models and tunnel models inside the spatial database is established to quantify the difficulty of the attack. Furthermore, the scenarios of the victim can be classified into high-risk and low-risk scenarios. When the vehicle is just out of the tunnel or in open scenarios, attackers can select these high-risk scenarios and implement aggressive spoofing attacks. Then the efficiency of the GNSS spoofing attack can be significantly improved. Finally, the proposed attack scheme is demonstrated by actual world data with simulated spoofing attacks in urban areas.

Research on GNSS Spoofing Mitigation Technology Based on Spoofing Correlation Peak Cancellation

In this letter, we propose a Global navigation satellite system (GNSS) spoofing suppression method based on spoofing correlation peak cancellation (SCPC). The approach estimates the spoofing signal from the baseband sampling sequence, and generates a reverse cancellation sequence to suppress GNSS spoofing attack. Based on this, a receiver scheme with SCPC function is proposed by adding a suppression module to the general GNSS receiver model. The experimental verification is conducted based on the TEXBAT dataset. By comparing the correlation peaks, carrier-to-noise ratio and peak trajectories of spoofed, mitigated and non-spoofed clean data, the results demonstrate that SCPC can correct the spoofing mixed navigation signals and effectively suppress spoofing attack.

Machine Learning-Based Screening and Measurement to Measurement Association for Navigation in GNSS Spoofing Environment

Global navigation satellite system (GNSS) provides reliable positioning across the globe. However, GNSS is vulnerable to deliberate interference problem like spoofing, which can cause fake navigation. This article proposes navigation in a GNSS spoofing environment by taking the received power, correlation distortion function, and pseudorange measurement observation space into account. In the proposed approach, both actual and interference measurements are considered a set. Machine learning screens the authentic measurements from the accessible set using parameters such as received power and correlation function distortion. To maintain the track and navigate the GNSS’s time-varying kinematics, we used a combination of the gating technique within the Kalman filter framework and logic-based track management. The machine learning classifiers like support vector machines (SVMs), neural networks (NNs), ensemble, nearest neighbor, and decision trees are explored, and we observe that linear SVM and NN provide a test accuracy of 98.20%. A time-varying position-pull off strategy is considered, and the metrics like position RMSE and track failure are compared with the conventional M-best algorithm. The results show that for four authentic measurements and spoof injections, there are only a few track failures. In contrast, even with an increase in spoof injections, track failures are zero in the case of six authentic measurements.

Analytic Models of a Loosely Coupled GNSS/INS/LiDAR Kalman Filter Considering Update Frequency Under a Spoofing Attack

Hostile spoofing attacks on the global navigation satellite system (GNSS) receiver increase the risk of catastrophic consequences to autonomous driving systems. This article addresses the problem of the vulnerability of the Kalman filter (KF) under spoofing attack. A state-of-the-art spoofing attack method based on maximizing the lateral deviation is utilized for verification and analysis. To analyze the vulnerability in actual road scenarios better, an analytic error model of the mechanism of GNSS spoofing is derived. Except for the uncertainty of the initial MSF state, the uncertainty of light detection and ranging (LiDAR), and the uncertainty of GNSS, a new factor in spoofing attacks, the update frequency of different sensors, is investigated in this article, which, in fact, is a key factor to increase the immunity multisensors’ fusion (MSF) systems. Experiments were performed in a typical urban scenario of the KAIST dataset. When the update frequency ratios between GNSS and LiDAR are 1, 2, 5, and 10, successful spoof attacks can be performed if the standard deviation (STD) of GNSS is smaller than 4, 2.7, 1.1, and 0.7 m, respectively. Therefore, experiments confirm that the uncertainty of GNSS and the update frequency ratio between LiDAR and GNSS are critical for spoofing attacks, which provides an indication for designing a defense strategy in the future.

DOA Estimation under GNSS Spoofing Attacks Using a Coprime Array: From a Sparse Reconstruction Viewpoint

The antispoofing method using the direction-of-arrival (DOA) feature can effectively improve the application security of the global navigation satellite system (GNSS) receivers. In this paper, a sparse reconstruction approach based on a coprime array of antennas is proposed to provide reliable DOA estimation under a GNSS spoofing attack. Specifically, the self-coherence property of genuine satellite signals and spoofing was fully exploited to construct a denoised covariance matrix that enables DOA estimation before receiver despreading. Based on this, an equivalent uniform linear array (ULA) was generated from the constructed covariance matrix via virtual array interpolation. By applying the ideal of sparse reconstruction to an equivalent ULA signal, the preliminary DOA estimation results could be obtained without the need for a number of signals. Considering that the sparse estimation technique suffers from basis mismatch effects, we designed an optimization problem with respect to off-grid error to compensate the initial DOA such that the performance loss of DOA estimation could be reduced. Numerical examples demonstrated the advantages of the proposed method in terms of degrees-of-freedom (DOFs), resolution and accuracy.

Detection and Mitigation of GNSS Spoofing Attacks in Maritime Environments Using a Genetic Algorithm

Due to the high reliance of daily activities on the Global Navigation Satellite System (GNSS), its security is one of the major concerns for research and industry. Most navigation and mobile-driven location-based services use GNSS to render services. Due to the low power and easy access of GNSS signals, these signals are vulnerable to spoofing and other types of attacks. Recently many GNSS spoofing attacks have been identified in road- and maritime-based environments. This study provides a technique to detect and counter the GNSS spoofing attack in the maritime environment. This technique uses the Receiver Autonomous Integrity Monitoring (RAIM) model with Least Square Estimation (LSE) and Proportional Integral Derivative (PID) Control to detect the spoofing attack. The proposed technique is based on the concept of a genetic algorithm and navigation devices, such as inertial sensors and pilot options for the ship. A case study using the AIS dataset and simulation using MATLAB and NS3 is provided to validate the performance of the proposed approach. Nine different voyages from the AIS dataset were considered to check the accuracy and performance of the proposed algorithm. The accuracy of the proposed technique was analyzed using the correctly identified attack. The result shows that the proposed technique identifies spoofing attacks with an average value of 90 percent. For result analysis the considered nine routes were traversed multiple times. Root mean square error is used to calculate the positional mismatch (error rate). Based on the combined results analysis, the average value of RMSE is 0.28. In a best-case scenario, the proposed approach provides an RMSE value of 0.009.

GNSS Multiparameter Spoofing Detection Method Based on Support Vector Machine

The vulnerability of the global navigation satellite system (GNSS) to spoofing limits its vast application in military safety and the national economy. Therefore, it is significantly important to rapidly and accurately detect GNSS spoofing. The traditional spoofing detection mainly detects spoofing signal intrusion by individual parameters such as signal power and signal quality. The single-parameter detection method can no longer manage complex and changing scenarios with the continuous development of spoofing technology. This paper proposes a GNSS multi-parameter joint detection method based on the support vector machine (SVM). The effects of spoofing on the signal acquisition, signal tracking, and position, velocity and time (PVT) solution processes are analyzed, and the composite signal quality monitoring (SQM), carrier-to-noise ratio C/N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> , pseudo-range Doppler consistency, PVT solving residuals, and clock difference and clock drift are extracted as detection features for training and testing of the support vector machine binary classification model. The F1-score of all nine-types parameter detection methods on TEXBAT and OAKBAT datasets improved by 22.95% and 19.6% (reach 93.97% and 97%), respectively, compared with only SQM parameters selected method. The obtained results demonstrate significant improvement in the spoofing detection performance compared with the traditional single-parameter methods.

A Slowly Varying Spoofing Algorithm Avoiding Tightly-Coupled GNSS/IMU With Multiple Anti-Spoofing Techniques

Vehicle and airborne navigation users are facing more and more complex signal interference and even spoofing. If vehicles and aircraft do not strengthen their anti-spoofing ability, their navigation performance is bound to be adversely affected. global navigation satellite system (GNSS) spoofing technology has gradually become a preferred interference method for spoofer because of its high concealment and great harm. For spoofer, user terminal increasingly adopts GNSS with inertial measurement unit (IMU): tightly-coupled GNSS/IMU, on this basis, user also configures a variety of anti-spoofing techniques to effectively deal with spoofing. Even if spoofer slowly changes user's positioning, if spoofing strategy is unreasonable, it will lead to the violation of parameter rationality of coupled filter output parameters and spoofing observation, which greatly increases the difficulty of spoofing. In view of the above problems, from the perspective of spoofer, in order to effectively counter the non cooperative target of assembling tightly-coupled GNSS/IMU by using GNSS spoofing, this paper establishes GNSS spoofing mathematical model, and proposes a slowly varying spoofing algorithm to avoid tightly-coupled GNSS/IMU with multiple anti-spoofing techniques based on the analysis of the influence mechanism of spoofing on the positioning of tightly-coupled GNSS/IMU, the algorithm proposes a measurement deviation determination method to avoid a variety of anti-spoofing techniques, which can gradually pull the positioning results of coupled system, and successfully avoid anti-spoofing techniques detection of least squares residual receiver autonomous integrity monitoring (RAIM) and parameter rationality check. The experimental results show that the algorithm can gradually change positioning of tightly-coupled GNSS/IMU within 30 s, and the north, east and down displacements basically achieve the spoofing effect, the errors with the expected offset are −0.5 m, 1.9 m and 12.7 m respectively. At the same time, the detection of the above anti-spoofing techniques is avoided. The mean value of test statistics for tightly-coupled system is reduced by 75.4% and does not exceed the alarm threshold, so as to achieve the purpose of spoofing, the effectiveness and high concealment of the spoofing algorithm are proved.

Localizing GNSS Spoofing Attacks Using Direct Position Determination

Global Navigation Satellite System (GNSS) receivers are vulnerable to all types of interferences due to the inherently low power of GNSS signals. Whereas GNSS jammers aim at denial-of-service attacks, GNSS spoofers bring even more risks, since they can fabricate a fake position and/or time without recognizing it. This paper presents a direct position determination method to improve the localization accuracy of GNSS spoofing attacks, which is called despreading direct position determination (DS-DPD). The localization algorithm utilizes a prior knowledge of the satellites’ code sequences, which in turn provides significant gains in localization accuracy. Firstly, the received signal model is established, which takes the time delay, Doppler shift, direction-of-arrival (DOA), and modulation codes into account. Then, the maximum likelihood (ML) criterion is utilized to construct the objective function of DS-DPD. Finally, the location parameters of the spoofers can be obtained through a two-dimensional spectral search of the objective function. Numerical simulations verify the localization performance improvement of the proposed DS-DPD algorithm. Especially when the interference-to-noise ratio (INR) approaches −30dB, the localization accuracy could be improved by more than ten times due to its full utilization of the delay, Doppler shift, DOA, and code sequences information.

GNSS spoofing detection technology based on Doppler frequency shift difference correlation

Global navigation satellite system (GNSS) spoofing interference poses a great threat to the security of end users. Based on the same propagation path characteristics of the spoofing signals transmitted by a single antenna spoofing device, this paper proposes a method against single antenna spoofing jamming utilizing the Fréchet distance of Doppler frequency difference. When the receiver moves, the Doppler data in a window are fitted via the leastsquares method, and the Fréchet distance between the two satellite signals is calculated to obtain the similarity evaluation value between them. The detection of spoofing signal is carried out based on the evaluation value. We use real data to verify the detection performance of the method, and the experimental results show that the method can effectively distinguish the spoofing signal from the authentic signal. In addition, the method has low computational complexity and requires less additional information, which makes it possible to apply it in the anti-spoofing module of a GNSS receiver.

A New Induced GNSS Spoofing Detection Method Based on Weighted Second-Order Central Moment

Global navigation satellite system (GNSS) spoofing causes the victim receiver to deduce false positioning and timing data; this notably threatens navigational safety. Thus, anti-spoofing techniques that improve the reliability of GNSS systems, for which interference detection is critical, are essential. Based on the distortion of tracking loop correlation function symmetry of the target receiver caused by gradual adjustment of induced spoofing signals, we proposed a new induced spoofing detection method that uses the weighted second-order central moment (WSCM) difference in the time-domain transient response of multiple correlators of the left and right peaks to obtain the test statistic, theoretically proving that the test statistic follows Gaussian distribution. The Neyman-Pearson hypothesis test method is used to determine the optimal test threshold and determine whether the receiver is being spoofed. The proposed WSCM-based method for spoofing detection was compared with three conventional methods in Scenarios 4 and 7 of the Texas Spoofing Test Battery database, showing that the detection probability of the proposed method is at least 24.15% higher at a false alarm rate of 10% and is more advantageous at lower false alarm rates and the alert time is shortened by at least 30 seconds, enabling at least a 20% faster detection efficiency. The proposed method overcomes the problem of existing methods, which are associated with difficulties in capturing the subtle time-varying effects of the relative carrier phase between the spoofing and authentic signals; thus, it provides excellent detection accuracy and effectiveness, showing broad potential applicability in GNSS spoofing detection.

A Slowly Varying Spoofing Algorithm on Loosely Coupled GNSS/IMU Avoiding Multiple Anti-Spoofing Techniques.

When satellite navigation terminal sensors encounter malicious signal spoofing or interference, if attention is not paid to improving their anti-spoofing ability, the performance of the sensors will be seriously affected. The global navigation satellite system (GNSS) spoofing has gradually become a research hotspot of the jammer because of its great harm and high concealment. In the face of more and more sensors coupling GNSS and inertial measurement unit (IMU) to varying degrees and configuring a variety of anti-spoofing techniques to effectively detect spoofing, even if the spoofer intends to gradually pull the positioning results, if the spoofing strategy is unreasonable, the parameters of the coupled filter output and spoofing observation measurement will lose their rationality, which will lead to the spoofing being detected. To solve the above problems, in order to effectively counter the non-cooperative target sensors of assembling loosely coupled GNSS/IMU using GNSS spoofing, based on the analysis of the influence mechanism of spoofing on the positioning of loosely coupled GNSS/IMU, a slowly varying spoofing algorithm to avoid loosely coupled GNSS/IMU with multiple anti-spoofing techniques is proposed in this paper, and a measurement deviation determination method to avoid multiple anti-spoofing techniques is proposed, which can gradually pull the positioning results of the coupled system and successfully avoid the detection of anti-spoofing techniques of innovation sequence monitoring and a rationality check on parameters. Simulation experimental results show that the proposed algorithm gradually changes the positioning of loosely coupled GNSS/IMU, the north and east displacements achieve the purpose of spoofing, and error with expected offset is −0.2 m and 2.3 m, respectively. Down displacement also basically achieves the purpose of spoofing, and error with the expected offset is 13.2 m. At the same time, the spoofer avoids the detection of multiple anti-spoofing techniques, does not trigger the system alarm, and realizes the purpose of spoofing; thus, the effectiveness and high concealment of the spoofing algorithm are verified.

A Steady-State Spoofing Detection and Exclusion Method Based on Raw IMU Measurement

GNSS (Global Navigation Satellite System) spoofing has become a great threat in recent years because of its elusiveness and harmfulness. For anti-spoofing usages, utilization of additional independent sensors is a preferred choice. In this work we develop a MEMS (Micro-Electro-Mechanical-Systems) IMU (Inertial Measurement Unit) based spoofing detection and exclusion method by first analyzing the relationship between the Doppler frequency from each navigation signal and the output from the IMU and then evaluating the residual. The detector is a steady-state spoofing detector which can provide continual anti-spoofing result throughout the spoofing attack, as it only requires raw measurements from the two sensors and a rather rough prior knowledge of the position of the host. Simulations are conducted to verify the theoretical derivation and to evaluate the anti-spoofing performance of the proposed method. Field experiments are carried out and the experiment results are analyzed, in which the proposed steady-state detector exhibits improved ability of spoofing identification over traditional methods under continuous spoofing attacks, by clearly distinguishing the authentic navigation signals from the counterfeited ones. Moreover, both the simulation and the field experiment demonstrate that a prior knowledge of the position of the host with the uncertainty of hundreds of kilometers, which can be readily obtained from various methods, is acceptable for the proposed detector.