• Journal of Positioning, Navigation, and Timing
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• v.1 no.1
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• pp.15-21
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• 2012

For a GNSS receiver's robustness against RFI and the high accuracy of navigation solution in GNSS, interference source detection and mitigation are needed. In this paper, an adaptive lattice IIR notch filter is employed to track single-tone continuous wave and swept continuous wave interference signals, and an interference detection method is proposed. Furthermore, this paper presents interference source characterization algorithm using multiple ground stations' interference detection results. The measurement of the signal powers from each ground station is used to build weighting factors to estimate the type of the interference. The performance of interference detection algorithm is simulated for scenarios of GPS signal in the presence of single-tone continuous wave interference and swept continuous wave interference.

• Journal of Communications and Networks
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• v.18 no.2
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• pp.210-217
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• 2016

In this paper, we propose a low complexity multiple-input multiple-output (MIMO) detection algorithm with adaptive interference mitigation in downlink multiuser MIMO (DL MU-MIMO) systems with quantization error of the channel state information (CSI) feedback. In DL MU-MIMO systems using the imperfect precoding matrix caused by quantization error of the CSI feedback, the station receives the desired signal as well as the residual interference signal. Therefore, a complexMIMO detection algorithm with interference mitigation is required for mitigating the residual interference. To reduce the computational complexity, we propose a MIMO detection algorithm with adaptive interference mitigation. The proposed algorithm adaptively mitigates the residual interference by using the maximum likelihood detection (MLD) error criterion (MEC). We derive a theoretical MEC by using the MLD error condition and a practical MEC by approximating the theoretical MEC. In conclusion, the proposed algorithm adaptively performs interference mitigation when satisfying the practical MEC. Simulation results show that the proposed algorithm reduces the computational complexity and has the same performance, compared to the generalized sphere decoder, which always performs interference mitigation.

• International Journal of Aeronautical and Space Sciences
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• v.13 no.4
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• pp.491-498
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• 2012

A Ground Based Augmentation System (GBAS) is an enabling technology for an aircraft's precision approach based on a Global Navigation Satellite System (GNSS). However, GBAS is vulnerable to interference, so effective GNSS interference detection and mitigation methods need to be employed. In this paper, an intentional GNSS interference detection and characterization algorithm is proposed. The algorithm uses Automatic Gain Control (AGC) gain and adaptive notch filter parameters to classify types of incoming interference and to characterize them. The AGC gain and adaptive lattice IIR notch filter parameter values in GNSS receivers are examined according to interference types and power levels. Based on those data, the interference detection and characterization algorithm is developed and Monte Carlo simulations are carried out for performance analysis of the proposed method. Here, the proposed algorithm is used to detect and characterize single-tone continuous wave interference, swept continuous wave interference, and band-limited white Gaussian noise. The algorithm can be used for GNSS interference monitoring in an excessive Radio Frequency Interference environment which causes loss of receiver tracking. This interference detection and characterization algorithm will be used to enhance the interference mitigation algorithm.

• Journal of Information Processing Systems
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• v.17 no.5
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• pp.933-946
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• 2021

In the non-orthogonal multiple access (NOMA) system, multiple user signals on the single carrier are superimposed in a non-orthogonal manner, which results in the interference between non-orthogonal users and noise interference in the channel. To solve this problem, an improved algorithm combining regularized zero-forcing (RZF) precoding with minimum mean square error-serial interference cancellation (MMSE-SIC) detection is proposed. The algorithm uses RZF precoding combined with successive over-relaxation (SOR) method at the base station to preprocess the source signal, which can balance the effects of non-orthogonal inter-user interference and noise interference, and generate a precoded signal suitable for transmission in the channel. At the receiver, the MMSE-SIC detection algorithm is used to further eliminate the interference in the signal for the received superimposed signal, and reduce the calculation complexity through the QR decomposition of the matrix. The simulation results show that the proposed joint detection algorithm has good applicability to eliminate the interference of non-orthogonal users, and it has low complexity and fast convergence speed. Compared with other traditional method, the improved method has lower error rate under different signal-to-interference and noise ratio (SINR).

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.39 no.3
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• pp.51-58
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• 2002

The conventional code division multiple access(CDMA) detector shows severe degradation in communication quality as the number of users increases due to multiple access interferences(MAI). This problem thus restricts the user capacity. Various multiuser detection algorithms have been proposed to overcome the MAI problem. The existing detectors can be generally classified into one of the two categories : linear multiuser detection and subtractive interference cancellation detectors. In the linear multiuser detection, a linear transform is applied to the soft outputs of the conventional detector. In the subtractive interference cancellation detection, estimates of the interference are generated and subtracted out from the received signal. There has been great interest in the family of the subtractive interference cancellation detection because the linear multiuser detection exhibits the disadvantage of taking matrix inversion operations. The successive interference cancellation (SIC) and the parallel interference cancellation (PIC) are the two most popular structures in the subtractive interference cancellation detector. The SIC structure is very simple in hardware complexity, but has the disadvantage of increased processing delay time, while the PIC structure is good in performance, but shows the disadvantage of increased hardware complexity. In this paper we propose a mixed structure form of SIC and PIC in order to achieve good performance as well as simple hardware complexity. A performance analysis of the proposed scheme has been made, and the superior characteristics of the mixed structure are demonstrated by extensive computer simulations. 

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.1
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• pp.42-48
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• 2006

In this paper a joint detection method for other cell interference cancellation is proposed in the next generation hybrid TD-CDMA mobile communication systems. A joint detection technique, a most characteristic feature of hybrid TD-CDMA mobile communication systems. retrieves users' data in the same time slot simultaneously with the elimination of multiple user interference. Previously a two stage joint detection method was proposed to cancel other cell interference as well as multiple user interference in the target cell. However the previous scheme does not have concrete ways to recognize other cell users who give major interference to the target cell. Thus all users in neighbor other cells has to be jointly detected and it causes huge complexity of the two stage joint detection. In this paper a method is proposed to perform two stage joint detection according to users' interference with the target cell. Performances of the proposed scheme are investigated through simulations and compared to the previous method the proposed method has no performance degradation and also lower the complexity of two stage joint detection significantly.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.4
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• pp.434-441
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• 2014

Recently, a mutual interference threat has been increasing among the radar systems due to the rapid growth of the military radar operation. In this paper, the radar interference protection criteria is presented for interoperability in terms of the radar coverage and target detection probability in association with the international recommendation on the interference spectrum by ITU-R. The required criteria for the minimum allowable interference is also presented in terms of INR. In order to ensure the maximum detection probability of the radar under the mutual interference situation, only 5 % of detection range loss is allowed for the case of INR of -6 dB, and required SNR is presented at each INR in terms of the detection range and detection probability. This result will be useful for establishing the interference protection criteria in the combined military radar systems.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.9
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• pp.723-732
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• 2016

This paper proposes an approach to fused navigation of an unmanned surface vehicle(USV) and to detection of the outlier or interference of global positioning system(GPS). The method fuses available sensor measurements through extended Kalman filter(EKF) to find the location and attitude of the USV. The method uses error covariance of EKF for detection of GPS outlier or interference. When outlier or interference of the GPS is detected, the method excludes GPS data from navigation process. The measurements to be fused for the navigation are GPS, acceleration, angular rate, magnetic field, linear velocity, range and bearing to acoustic beacons. The method is tested through simulated data and measurement data produced through ground navigation. The results show that the method detects GPS outlier or interference as well as the GPS recovery, which frees navigation from the problem of GPS abnormality.

• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.1
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• pp.43-62
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• 2017

Mobile pulse scanning Light Detection And Ranging (LIDAR) are essential components of intelligent vehicles capable of autonomous travel. Obstacle detection functions of autonomous vehicles require very low failure rates. With the increasing number of autonomous vehicles equipped with scanning LIDARs to detect and avoid obstacles and navigate safely through the environment, the probability of mutual interference becomes an important issue. The reception of foreign laser pulses can lead to problems such as ghost targets or a reduced signal-to-noise ratio. This paper will show the probability that any two scanning LIDARs will interfere mutually by considering spatial and temporal overlaps. We have conducted four experiments to investigate the occurrence of the mutual interference between scanning LIDARs. These four experimental results introduced the effects of mutual interference and indicated that the interference has spatial and temporal locality. It is hard to ignore consecutive mutual interference on the same line or the same angle because it is possible the real object not noise or error. It may make serious faults because the obstacle detection functions of autonomous vehicle rely on heavily the scanning LIDAR.

• Journal of the Korean institute of surface engineering
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• v.55 no.3
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• pp.156-163
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• 2022

An ammonium ion with a size and charge similar to that of potassium can bind to valinomycin, which is used as an ion carrier for potassium, and cause a meaningful interference effect on the detection of potassium ions. Currently, there are few ion sensors that correct the interference effect of ammonium ions, and there are few studies that specifically suggest the mechanism of the interference effect. By fabricating a SPCE-based potassium ion-selective electrode, the electromotive force was measured in the concentration range of potassium in the nutrient solution, and the linear range was measured to be 10^-5 to 10^-2 M, and the detection limit was 10^-5.19 M. And the interference phenomenon of the potassium sensor was investigated in the concentration range of ammonium ions present in the nutrient solution. Therefore, a data-based analysis strategy using deep learning was presented as a method to minimize the interference effect.