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Block diagram of a DS/BPSK system, including interference suppression in the receiver.
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A new algorithm for narrowband interference suppression in direct-sequence spread-spectrum (DS-SS) communications is presented. The algorithm combines the undecimated wavelet packet transform (UWPT) with frequency shifts to confine the interference energy in a subband that is subsequently eliminated. Computer simulation shows a robust performance t...
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Citations
... The accuracy of navigation and tracking systems depends on the accuracy of received GPS signals which, due to their weak power, are vulnerable to external interference such as jamming and spoofing (Ioannides et al. 2016). Various methods have been proposed to mitigate GPS jamming (Ioannides et al. 2016), which include the adaptive filtering method (Borio et al. 2008;Mao et al. 2011;Chien et al. 2013), wavelet packet transform (Pardo et al. 2006;Mosavi et al. 2017), combined wavelet transform and filtering (Chen et al. 2016), wavelet-based correction (Mosavi et al. 2011), and artificial neural networks for interference rejection/suppression (Mao 2008;Mosavi and Shafiee 2016). ...
A challenging and outstanding problem in applications that involve or rely on GPS signals is to mitigate jamming. We develop a machine learning-based antijamming framework for GPS signals. Three types of jamming signals are considered: continuous wave interference, chirp and pulse jamming. In addition, white Gaussian noise is assumed to be present. From the point of view of communication, information is encoded in the coarse/acquisition (C/A) code. Multiplying the jammed signal by a sinusoidal wave and integrating over one C/A code period leads to a jammed C/A code signal. To mitigate jamming, we study three types of machine learning methods: reservoir computing (echo state network), multi-layer perceptron, and long short-term memory networks (RNNs). A machine can be trained to learn and predict the signal directly or learn and predict jamming where the real signal can be obtained by removing the jammed component from the total received signal. For a high-frequency carrier (e.g., the standard 1575.42 MHz L1 carrier), learning and prediction can be made computationally efficiently on the C/A code signal. The main result is that machine learning can be effective for predicting and extracting weak GPS signals even in a strongly jammed/noisy environment where the jamming amplitude is three orders of magnitude stronger than the GPS signal. We find that the reservoir computing scheme is stable and performs well for all three types of jamming. The multi-layer perceptron is better for predicting the jamming signal than the GPS signal itself, and the long short-term memory networks work well but only for certain jamming types. In particular, with the direct signal prediction method, the bit error rate (BER) associated with reservoir computing (RC) remains at near-zero values (less than 1%) even for jamming signal ratio (JSR) up to 60 dB for the three types of jamming. The multi-layer perceptron (MLP) method breaks down when the JSR is larger than 20 dB for continuous wave interference (CWI) and pulse jamming, 45 dB for chirp jamming. The long short-term memory (LSTM) can perform very well for the chirp jamming with a near zero error rate and give BER larger than 10% when the JSR is around 40 dB for the CWI and pulse jamming. For the jamming prediction method (indirect method), these three machine learning methods perform well, with near-zero BER (less than 1%). Overall, the RC scheme is stable and performs well for three types of jamming. Besides, RC is fast compared to LSTM method, with much less running time.
... The UWPT has total benefits of the DWPT and also resolves the issue of less output wavelet coefficients. Because of its better performance, UWPT has been used in the many field of electrical engineering [15]- [17]. In the UWPT, re-scaling of the wavelet filter coefficients is needed to preserve the energy of wavelet coefficients according to following equations. ...
Abstract - In this paper, a method is presented for visualization
of time-varying power quality disturbances in electrical power
distribution system using undecimated wavelet packet transform
(UWPT). The proposed method decomposes the input signal in
various frequency bands and provides clear visualization of
fundamental and each harmonic components. The UWPT is a
time-invariant transform, which can lead to better understanding
of time-dependent power quality disturbances. Various type of
stationary and time-varying waveforms have been used to show
the effectiveness of the proposed scheme. The results confirm that
the proposed technique based on UWPT efficiently decomposes
the fundamental and harmonics component from the distorted
signal, reflecting its suitability for power quality monitoring and
analysis.
Index Terms— Undecimated wavelet packet transform (UWPT),
Quadrature mirror filter (QMF), finite impulse response (FIR)
filter, power quality.
... , like Short Time Fourier Transform (STFT) based processing [9,10], filter banks [11], Wavelet Transform (WT) [12][13][14] and subspace processing [15,16] are well suited for low cost and low power applications [8,13]. These techniques study a signal in both time and frequency domains simultaneously. ...
... , like Short Time Fourier Transform (STFT) based processing [9,10], filter banks [11], Wavelet Transform (WT) [12][13][14] and subspace processing [15,16] are well suited for low cost and low power applications [8,13]. These techniques study a signal in both time and frequency domains simultaneously. ...
... However, they have advantages such as minimum signal distortion, low power, and low cost implementation. In the wavelet analysis, the use of scalable modulated window solves the signal-cutting problem of STFT and the filter bank and provides a flexible resolution in both time and frequency domains [12][13][14]. ...
Interference mitigation is an important issue for global positioning system receivers. An anti-jamming system is proposed, which employs two wavelet packet transform (WPT)-based interference mitigation blocks. The proposed pre-/post-correlation mitigation technique employs lower decomposition levels for the WPT-based denoising algorithms because it shares the responsibility of the interference mitigation between two blocks. Moreover, the first block can be deactivated in low-power jamming situations. The performance of the anti-jamming system is evaluated for the cases of single-tone continuous wave interference and linear chirp interference. Experiments and theory prove that the computational cost of the proposed method is significantly less than similar WPT-based mitigation methods and thus it is a fast interference mitigation technique. Experiments also show that it has a considerable decrease in terms of positioning error and thus it is an accurate suppression method.
... , like Short Time Fourier Transform (STFT) based processing [9,10], filter banks [11], Wavelet Transform (WT) [12][13][14] and subspace processing [15,16] are well suited for low cost and low power applications [8,13]. These techniques study a signal in both time and frequency domains simultaneously. ...
... , like Short Time Fourier Transform (STFT) based processing [9,10], filter banks [11], Wavelet Transform (WT) [12][13][14] and subspace processing [15,16] are well suited for low cost and low power applications [8,13]. These techniques study a signal in both time and frequency domains simultaneously. ...
... However, they have advantages such as minimum signal distortion, low power, and low cost implementation. In the wavelet analysis, the use of scalable modulated window solves the signal-cutting problem of STFT and the filter bank and provides a flexible resolution in both time and frequency domains [12][13][14]. ...
This paper proposes a new method for rejecting the Continuous Wave Interferences (CWI) in the Global Positioning System (GPS) receivers. The proposed filter is made by cascading an adaptive Finite Impulse Response (FIR) filter and a Wavelet Packet Transform (WPT) based filter. Although adaptive FIR filters are easy to implement and have a linear phase, they create self-noise in the rejection of strong interferences. Moreover, the WPT which provides detailed signal decomposition can be used for the excision of single-tone and multi-tone CWI and also for de-noising the retrieved GPS signal. By cascading these two filters, the self-noise imposed by FIR filter and the remaining jamming effects on GPS signal can be eliminated by the WPT based filter. The performance analysis of the proposed cascade filter is presented in this paper and it is compared with the FIR and the WPT based filters. Experimental results illustrate that the proposed method offers a better performance under the interference environments of interest in terms of the signal-to-noise ratio gain and mean square error factors compared to previous methods. © 2016, Iran University of Science and Technology. All rights reserved.
... As is known to all, the wavelet packet decomposition usually includes regular decomposition 3rd International Conference on Mechatronics and Information Technology (ICMIT 2016) with uniform sub-band and optimal wavelet packet decomposition with uneven sub-band [5,6]. The common interference locating methods based on wavelet packet include sub-band power ratio node positioning [7], adaptive threshold positioning [8] and so on. A new method for interference suppression has been put forward based on the optimum wavelet packet decomposition. ...
... Various types of interference can be mitigated by WT due to its multi-resolution time-frequency decomposition, but there is also the limitation of the fixed spectral part which causes some problems such as interband spectral leakage and fixed time-frequency resolution. An evolution of the WT is the wavelet packet transform (WPT) (Pardo et al. 2006). It can be adapted and switched between time and frequency methods depending on the kind of interference, so it provides better performance than previous transforms. ...
... Various kinds of interference have different energy distribution which determines the mitigation domain. For example, narrowband interference suppression is easier in the frequency domain because the energy is localized in frequency and expanded in time (Pardo et al. 2006;Simone and Caselli 2008). ...
Since the Global Positioning System (GPS) satellites broadcast signals travel a long distance, the received signals are attenuated below the thermal noise level. Such weak signals are seriously subject to intentional or unintentional interferences from hostile or friendly noise sources. We propose an NN-based predictor for GPS anti-jamming applications. This new method exploits the adaptive notch filter as a cascade filter and the simple structure of Sigma-Pi neural network (Σ-Π NN). The Σ-Π NN can be trained quickly while avoiding the huge exponential computation for updating weights and thresholds in each layer, which allows easy hardware implementation. Simulation results show that its signal-to-noise ratio (SNR) improvement factor exceeds the factors of conventional multilayer perceptron, recurrent neural network, and other compound methods in single-tone and multi-tone continuous wave interference environments. Besides improving SNR, the anti-jamming performances are evaluated by computing root mean squared (RMS) prediction error and space vehicle (SV) observation number. The proposed algorithm provides the desired SV observation number, even for more than four vehicles, increases SNR improvement by about 46 % on average, and reduces RMS by about 27 % in average in both jamming mitigation processes.
A narrowband interference (NBI) suppression method based on adaptive WPT is proposed. Firstly, the optimum parameters of the frequency shift and the highest resolution level are selected using Genetic algorithm. Then the adaptive wavelet packet decomposition based on parity checking is done to the shifted signal. Finally the interference-free signal is obtained by setting the sub-band with interference to zero and being reconstructed. Simulation results show that this algorithm can both suppress single tone and multi-tone interference effectively.
Accurate and fast estimation of time-varying harmonics are essential requirements for online monitoring, analysis, and control of electrical power system. This paper presents a fast algorithm based on the undecimated wavelet packet transform (UWPT) to estimate the amplitude of fundamental and harmonic components of stationary as well as a time-varying power signal. The UWPT uses only one cycle of the fundamental frequency for precise measurement of time-varying harmonics while their amplitude has been determined accurately utilizing the time-invariant property of the UWPT. The robustness and accuracy of the proposed technique have been investigated on synthetic as well as experimental test signals using MATLAB tool. Further, the UWPT algorithm has also been implemented on the Xilinx Virtex-6 FPGA ML-605 board, using XSG/ISE design suite 14.2 and its performance, in terms of hardware accuracy, resource utilization as well as timing requirements have been tested using the experimental test signal.
A new algorithm for narrowband interference suppression in Direct Sequence Spread Spectrum (DSSS) system is presented. The algorithm combines the optimum frequency shift and the Undecimated Wavelet Packet Transform (UWPT) to locate the interference energy in as little sub-band as possible. In addition, the adaptive algorithm is used to reduce the harm to the signal caused by eliminating the disturbed sub-band. Simulation results show that the proposed algorithm has a better performance than the traditional Undecimated Wavelet Packet Transform with frequency shift (SUWPT) algorithm in the suppression of the Multi-Tone Interference (MTI).
