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In practical airborne radar, the interference signals in training snapshots usually lead to inaccurate estimation of the clutter covariance matrix (CCM) in space-time adaptive processing (STAP), which seriously degrade radar performance and even occur target self-nulling phenomenon. To solve this problem, a knowledge-aided sparse recovery (SR) STAP algorithm based on Gaussian kernel function is developed. The proposed method distinguishes clutter components and interference signals in training snapshots by the priori knowledge that the clutter components are distributed along the clutter ridge, which dislodges interference signals from training snapshots by Gaussian kernel similar degree. Thus, the CCM is estimated by utilizing these snapshots. Finally, the proposed STAP weight vector is built, which is convenient for the subsequent signal processing. The experimental results were performed to verify the effectiveness and superiority of the proposed method. The test results also show that the proposed algorithm completely removes the interference signals, accurately estimates CCM, and improves the moving target detection performance in small-sample and non-homogeneous clutter environments.

Sometimes, it is impossible to conduct tests with the use of the GNSS system, or the obtained results of the measurements made differ significantly from the predicted accuracy. The most common cause of the problems (external factors, faulty results) are interference disturbances from other radio telecommunication systems. The subject of this paper is to conduct research, the essence of which is an in-depth analysis in the field of elimination of LTE interference signals of the GNSS receiver, that is based on the developed effective methods on counteracting the phenomenon of interference signals coming from this system and transmitted on the same frequency. Interference signals are signals transmitted in the GNSS operating band, and unwanted signals may cause incorrect processing of the information provided to the end-user about his position, speed, and current time. This article presents methods of identifying and detecting interference signals, with particular emphasis on methods based on spatial processing of signals transmitted by the LTE system. A comparative analysis of the methods of detecting an unwanted signal was made in terms of their effectiveness and complexity of their implementation. Moreover, the concept of a new comprehensive anti-interference solution was proposed. It includes, among others, information on the various stages of GNSS signal processing in the proposed system, in relation to the algorithms used in traditional GNSS receivers. The final part of the article presents the obtained research results and the resulting significant observations and practical conclusions.

Radio frequency identification (RFID) technology has widely been used in the last few years. Its applications focus on auto identification, tracking, and data capturing issues. However, RFID suffers from the main problem of tags collision when multiple tags simultaneously respond to the reader request. Many protocols were proposed to solve the collision problems with good identification efficiency and an acceptable time delay, such as the blocking anti-collision protocol (BA). Nevertheless, most of these protocols assumed that the RFID reader could decode the tag’s signal only when there was one tag responding to the reader request once each time. Hence, they ignored the phenomenon of the capture effect, which results in identifying the tag with the stronger signal as the multiple tags simultaneously respond. As a result, many tags will not be identified under the capture effect. Therefore, the purpose of this paper is to take the capture effect phenomenon into consideration in order to modify the blocking BA protocol to ensure a full read rate, i.e., identifying all the tags in the frame without losing any tag. Moreover, the modifications include distinguishing between collision and interference responses (for the period of staying tags) in the noisy environments, for the purpose of enhancing the efficiency of the identification. Finally, the simulation and analytical results show that our modifications and MBA protocol outperform the previous protocols in the same field, such as generalized query tree protocols (GQT1 and GQT2), general binary tree (GBT), and tweaked binary tree (TBT).

The backscattering from man-made point targets like passive corner reflectors and active transponders is often used as a radiometric calibration standard for synthetic aperture radar (SAR) calibration. As new systems emerge and the demand for more accurate systems increases, it becomes necessary to better understand the effects of real or imperfect targets on the radiometric calibration results. Therefore, a point-target SAR simulator is presented which models the complete external radiometric calibration process. It incorporates a number of target properties like frequency response, transponder internal calibration strategies, noise, and interference signals, and it takes the instrument SAR mode settings into consideration. Thereby, the relevant target backscatter variation as observed in the processed SAR image with respect to an ideal or any other target can be determined. The simulation results are relevant during the design process of a new target as well as during the actual calibration of a SAR system. Based on these point-target simulations, correction coefficients can be stated for each target and SAR mode, therefore decreasing the remaining radiometric point-target uncertainties. The quantitative examples in this paper show that these corrections can influence the absolute radiometric calibration by more than 1 dB. [ABSTRACT FROM AUTHOR]

During the process of coal road excavation, various interference signals, induced by environmental noise, drilling, and scraper loader, will affect the risk assessment of coal and gas outburst using acoustic emission (AE) and electromagnetic radiation (EMR) monitoring technology. To distinguish between different interference signals and danger signals, discrete wavelet transform (DWT) was used to decompose and reconstruct signals, and continuous wavelet transform (CWT) was used to obtain the time-frequency plane. The research results show that: (1) interference signals generally exhibit fluctuating changes within small ranges; in comparison, the intensity of AE and EMR signals caused by coal and rock fracture is found to continuously rise for a long period (longer than 2 h). (2) Different interference signals and danger signals differ significantly in their time-frequency plane. (3) Through decomposition and reconstruction of original signal, obvious precursor information can be found in the time-frequency plane of reconstructed signals. [ABSTRACT FROM AUTHOR]

Sometimes, it is impossible to conduct tests with the use of the GNSS system, or the obtained results of the measurements made differ significantly from the predicted accuracy. The most common cause of the problems (external factors, faulty results) are interference disturbances from other radio telecommunication systems. The subject of this paper is to conduct research, the essence of which is an in-depth analysis in the field of elimination of LTE interference signals of the GNSS receiver, that is based on the developed effective methods on counteracting the phenomenon of interference signals coming from this system and transmitted on the same frequency. Interference signals are signals transmitted in the GNSS operating band, and unwanted signals may cause incorrect processing of the information provided to the end-user about his position, speed, and current time. This article presents methods of identifying and detecting interference signals, with particular emphasis on methods based on spatial processing of signals transmitted by the LTE system. A comparative analysis of the methods of detecting an unwanted signal was made in terms of their effectiveness and complexity of their implementation. Moreover, the concept of a new comprehensive anti-interference solution was proposed. It includes, among others, information on the various stages of GNSS signal processing in the proposed system, in relation to the algorithms used in traditional GNSS receivers. The final part of the article presents the obtained research results and the resulting significant observations and practical conclusions. [ABSTRACT FROM AUTHOR]

Radio frequency identification (RFID) technology has widely been used in the last few years. Its applications focus on auto identification, tracking, and data capturing issues. However, RFID suffers from the main problem of tags collision when multiple tags simultaneously respond to the reader request. Many protocols were proposed to solve the collision problems with good identification efficiency and an acceptable time delay, such as the blocking anti-collision protocol (BA). Nevertheless, most of these protocols assumed that the RFID reader could decode the tag's signal only when there was one tag responding to the reader request once each time. Hence, they ignored the phenomenon of the capture effect, which results in identifying the tag with the stronger signal as the multiple tags simultaneously respond. As a result, many tags will not be identified under the capture effect. Therefore, the purpose of this paper is to take the capture effect phenomenon into consideration in order to modify the blocking BA protocol to ensure a full read rate, i.e., identifying all the tags in the frame without losing any tag. Moreover, the modifications include distinguishing between collision and interference responses (for the period of staying tags) in the noisy environments, for the purpose of enhancing the efficiency of the identification. Finally, the simulation and analytical results show that our modifications and MBA protocol outperform the previous protocols in the same field, such as generalized query tree protocols (GQT1 and GQT2), general binary tree (GBT), and tweaked binary tree (TBT). [ABSTRACT FROM AUTHOR]