Cancellation Method Research Articles

Bistatic Sea Clutter Suppression Method Based on Compressed Sensing Optimization

In order to reduce the sea clutter interference in the detection of sea surface targets, we propose a bistatic sea clutter suppression method based on compressed sensing optimization in this paper. The proposed method mitigates the interference effect by reconstructing and cancelling out the sea clutter. Since the fixed sparse base is not always completely applicable for the sparse representation of sea clutter, we propose a sparse base optimization algorithm based on transfer learning to convert the fixed sparse base into an adaptive one. Moreover, we introduce a sensing matrix optimization algorithm to decrease the cross-correlation coefficient between the measurement matrix and the sparse base matrix, which can enhance the signal reconstruction quality. Finally, we use the orthogonal matching pursuit algorithm to reconstruct the sea clutter and employ the reconstructed results to cancel and suppress the sea clutter. The simulation results demonstrate that the proposed method outperforms the traditional methods such as the root time-domain cancellation method and the singular value decomposition method (SVD). Therefore, the proposed method has great practical significance for the detection of bistatic sea surface targets.

Method for Digital Cancellation of System Interference in a Full-Duplex Power Line Communication System

Every year the number of IoT devices is growing, which gives a boost to development of such technology as Power Line Communication (PLC). The term PLC refers to the use of a power supply circuit to transmit data. Full-duplex technology can be applied to increase the data transfer rate in a PLC. The difficulty in using a full duplex is the need to suppress the transmitter’s own signal (interference signal). Analog cancellation and digital cancellation are used for this purpose. Common algorithms for digital cancellation are adaptive algorithms. In this paper adaptive algorithms such as Particle Swarm Optimization (PSO) and Recursive Least Squares (RLS) are considered and a modification of the classical RLS is proposed. The proposed algorithm uses precalculated weight coefficients together with periodic reinitialization of the filter. This avoids the influence of significant changes in the input signal on the further process of filter adaptation and provides the highest level of echo suppression. The proposed algorithm provides an improvement of parameters such as Error Vector Magnitude (EVM) and Signal-to-Interference Ratio (SIR) in comparison with classical RLS and PSO, according to the results of the study.

Time Synchronization and Integration of Bearing Fault Impacts upon Stator Currents

As regards bearing fault detection of induction motors using stator current, anything unrelated to the faults is the “noise”. The noise attenuation leads to an improved estimation of the bearing fault signal. The gist of this study is the integration and synchronization of the three residues obtained from the current noise cancelation methods: Time Shifting and Linear Prediction. This procedure results in a richer bearing fault signal than any of the individual residues through cross-correlation. The developed method efficiently synchronizes and integrates the current residues so that fault characteristic frequencies can be more conspicuous in spectral analysis. Both simulation and experimental results attest to the merit and effectiveness of the developed method in detecting both outer and inner race bearing faults.

A TDMA approach for OFDM-based multiuser RadCom systems

This paper is focused on the multiuser implementation of fusion of radar and communication (RadCom) in internet-of-vehicles (IoV) scenarios. Traditional time-division multiple access (TDMA) technology degrades the velocity detection performance of orthogonal frequency-division multiplexing (OFDM)-based RadCom systems. We propose a new TDMA approach for OFDM-based RadCom systems, where multiuser communication and radar detection are completed synchronously. We consider a continuous-wave TDMA OFDM structure in which random user data or Zadoff-Chu (ZC) sequences are transmitted in one symbol duration to ensure detection performance. As an application of interference cancellation method, user data demodulation and environment sensing can be simultaneously accomplished by our proposed approach. We carry out numerical evaluation and show wireless communication and radar detection performance over the continuous-wave TDMA OFDM-based RadCom approach.

Exponential Curve-Based Control Strategy for Auxiliary Equipment Power Supply Systems in Railways

An exponential curve-based (ECB) control strategy has been proposed in this paper. The proposed ECB control strategy is based on the growth and decay of charge in the series RC circuit and the harmonic elimination by detecting the Fourier expansion series of the auxiliary equipment power supply system’s (AEPSS) three-phase output voltage level. It can quickly adjust each duty cycle to the best value for driving the isolated three-phase inverter (ITPI) and produce a three-phase 380 VAC/60 Hz output. A comparison of the AEPSS output performance using the traditional voltage cancellation method (VCM) and the proposed ECB control strategy was performed. The hardware implementation of the system was performed on the prototype developed in the laboratory. These control strategies are tested under three conditions, i.e., (i) Vi = 550 VDC. (ii) Vi = 750 VDC. (iii) Vi = 800 VDC. The total harmonic distortion (THD) is 13.7%, 14.5%, and 14.9%, and the output voltage Vo is 372.3 VAC, 377.3 VAC, and 385.3 VAC using the traditional control strategy at three test conditions, respectively. However, the THD is 7.2%, 7.8%, and 8.0%, and the output voltage Vo is 382.2 VAC, 381.2 VAC, and 381.9 VAC using the proposed ECB control strategy under the test conditions. It is obvious from the hardware results that the output voltage harmonics and output voltage level for the proposed ECB control strategy are superior to the traditional VCM. The voltage produced from the AEPSS using the proposed ECB control strategy is more stable and has better quality. In addition, the filter size is also reduced.

Highly reconfigurable silicon integrated microwave photonic filter towards next-generation wireless communication

Integrated microwave photonic filters (IMPFs) are capable of offering unparalleled performances in terms of superb spectral fineness, broadband, and more importantly, the reconfigurability, which encounter the trend of the next-generation wireless communication. However, to achieve high reconfigurability, previous works should adopt complicated system structures and modulation formats, which put great pressure on power consumption and controlment, and, therefore, impede the massive deployment of IMPF. Here, we propose a streamlined architecture for a wideband and highly reconfigurable IMPF on the silicon photonics platform. For various practical filter responses, to avoid complex auxiliary devices and bias drift problems, a phase-modulated flexible sideband cancellation method is employed based on the intensity-consistent single-stage-adjustable cascaded-microring (ICSSA-CM). The IMPF exhibits an operation band extending to millimeter-wave (≥30 GHz), and other extraordinary performances including high spectral resolution of 220 MHz and large rejection ratio of 60 dB are obtained. Moreover, Gb/s-level RF wireless communications are demonstrated for the first time towards real-world scenarios. The proposed IMPF provides broadband flexible spectrum control capabilities, showing great potential in the next-generation wireless communication.

Development and experimental verification of an active noise cancellation (ANC) method for non-invasive sensing

Ultrasonic wave propagation may be used in non-invasive sensing to identify the properties of a fluid in a container. An ultrasonic excitation can be coupled into the liquid or the gas through the walls of the container and detected by a receiver on the other side. However, in addition to this fluid path, another signal will also propagate through the structure and is referred as noise in this study. For most materials, this structural noise will be of higher amplitude compared to the fluid signal due to the large acoustic impedance difference between the solid container and the fluid. In this paper, an active noise cancellation (ANC) method is developed and demonstrated on an experimental setup. It was shown that this method cancels more than 90% of the noise signal in a given time window of interest. A sequential version of this cancellation method is also proposed, and it was shown that its performance improves as the number of canceling excitations is increased. The performance was found to be independent of the location of canceling transducers and position of the silence window but dependent on the width of the silence window. As an example, the ANC method was applied to noise cancellation of a signal travelling through water in a stainless-steel container. The signal-to-noise ratio (SNR) of the water signal in the window of interest was increased by 148% from 13.98 dB to 34.68 dB by using the proposed ANC method.

A Linear Near-Field Interference Cancellation Method Based on Deconvolved Conventional Beamformer Using Fresnel Approximation

In underwater acoustic detection using towed arrays, the in-band radiation noise of the tow-ship generates significant interference. In this article, a high-resolution spatial filter based on the deconvolved conventional beamformer (dCv) is proposed to mitigate the impact of this noise on the detection on the beam of interest. The tow-ship interference is near field, thus, the dCv cannot be applied directly as the point spread function is shift variant. In this work, a solution to this problem involving the Fresnel approximation is developed. It is demonstrated analytically that the Fresnel approximation is not sensitive to the accuracy of the estimation of the interference range, and its applicability depends on the arrival angle of the interference. Experimental results show that the linearity of the dCv spatial filter ensures that the amplitude and phase of the array signal can be retrieved with no distortion, which is critical for acoustic detection.

Comments on “Common-Mode Noise Reduction by Parasitics Capacitance Cancellation in the Three-Phase Inverter”

This article comments on the published article titled “Common-mode noise reduction by parasitics capacitance cancellation in the three-phase inverter” authored by Zhang and Wu (2019). The three-terminal electromagnetic interference (EMI) filter can effectively suppress the EMI noise on the output side in the paper. The numerical analysis and the relationship of converting negative inductance into capacitance at high frequency are discussed in detail. Zhang and Wu (2019) presented a parasitic capacitance cancellation method to reduce the conducted emissions exiting a three-phase inverter. The idea of parasitic capacitance cancellation is not novel, and Wang and Lee (2007, 2010) originally applied it to reduce the common mode noise exiting a boost PFC converter. The parasitic capacitance cancellation of inductors is discussed in papers by Neugebauer and Perreault (2006) and Piboonwattanakit and Khan-Ngern (2008). These papers should be cited in the introduction and the references.

Joint Method of Moments (JMoM) and Successive Moment Cancellation (SMC) Multiuser Time Synchronization for ZP-OFDM-Based Waveforms Applicable to Joint Communication and Sensing

It has been recently shown that zero padding (ZP)-orthogonal frequency-division multiplexing (OFDM) is a promising candidate for 6G wireless systems requiring joint communication and sensing. In this paper, we consider a multiuser uplink scenario where users are separated in power domain, i.e., non-orthogonal multiple access (NOMA), and use ZP-OFDM signals. The uplink transmission is grant-free and users are allowed to transmit asynchronously. In this setup, we address the problem of time synchronization by estimating the timing offset (TO) of all the users. We propose two non-data-aided (NDA) estimators, i.e., the joint method of moment (JMoM) and the successive moment cancellation (SMC), that employ the periodicity of the second order moment (SoM) of the received samples for TO estimation. Moreover, the coding assisted (CA) version of the proposed estimators, i.e., CA-JMoM and CA-SMC, are developed for the case of short observation samples. We also extend the proposed estimators to multiuser multiple-input multiple-output (MIMO) systems. The effectiveness of the proposed estimators is evaluated in terms of lock-in probability under various practical scenarios. Simulation results show that the JMoM estimator can reach the lock-in probability of one for the moderate range of Eb/N0 values. While existing NDA TO estimators in the literature either offer low lock-in probability, high computational complexity that prevents them from being employed in MIMO systems, or are designed for single-user scenarios, the proposed estimators in this paper address all of these issues.

On the outage performance of multi-user NOMA system with adaptive SIC

The performance of non-orthogonal multiple-access (NOMA) is significantly determined by the successive interference cancellation (SIC) technique. However, the interference redundancy can happen during the NOMA receiver performing SIC. To tackle this issue, this paper proposes a novel adaptive successive interference cancellation (ASIC) method. Specifically, the decoding error is considered as interference during the SIC process, and an adaptive filter with various weights is introduced for detection error mitigation. For the multi-user downlink NOMA system, the outage probability is analyzed under conventional and the proposed SIC methods. Simulation results verify our analysis, which also demonstrate the superiority of the proposed ASIC method.

DRFM-Based Repeater Jamming Reconstruction and Cancellation Method with Accurate Edge Detection

Digital radio frequency memory (DRFM) based repeater jamming can create false targets, which can lead to a loss of situational awareness, misidentification of targets, and decreased overall performance of the radar system. Traditional jamming suppression methods do not give due importance to the accurate estimation of the jamming edge, resulting in jamming residual and poor anti-jamming performance. To tackle this issue, this paper explores the reason and impact of inaccurate jamming edge estimation and proposes a DRFM-based repeater jamming reconstruction and cancellation method with accurate edge detection. In the proposed method, firstly, multiple jamming parameters are obtained by computing the short-time fractional Fourier transformation (STFRFT) spectrogram of the received signal. To avoid jamming residue, the proposed method estimates the accurate jamming edges by the joint use of the difference of box (DOB) filters and time domain deconvolution (TDDC) curves. Numerical simulations and experiments are conducted to evaluate the algorithm’s effectiveness in countering smeared spectrum (SMSP) and interrupted sampling repeater jamming (ISRJ). The results demonstrate its superior jamming reconstruction and suppression performance than other methods.

Radar Human Activity Recognition with an Attention-Based Deep Learning Network

Radar-based human activity recognition (HAR) provides a non-contact method for many scenarios, such as human-computer interaction, smart security, and advanced surveillance with privacy protection. Feeding radar-preprocessed micro-Doppler signals into a deep learning (DL) network is a promising approach for HAR. Conventional DL algorithms can achieve high performance in terms of accuracy, but the complex network structure causes difficulty for their real-time embedded application. In this study, an efficient network with an attention mechanism is proposed. This network decouples the Doppler and temporal features of radar preprocessed signals according to the feature representation of human activity in the time-frequency domain. The Doppler feature representation is obtained in sequence using the one-dimensional convolutional neural network (1D CNN) following the sliding window. Then, HAR is realized by inputting the Doppler features into the attention-mechanism-based long short-term memory (LSTM) as a time sequence. Moreover, the activity features are effectively enhanced using the averaged cancellation method, which improves the clutter suppression effect under the micro-motion conditions. Compared with the traditional moving target indicator (MTI), the recognition accuracy is improved by about 3.7%. Experiments based on two human activity datasets confirm the superiority of our method compared to traditional methods in terms of expressiveness and computational efficiency. Specifically, our method achieves an accuracy close to 96.9% on both datasets and has a more lightweight network structure compared to algorithms with similar recognition accuracy. The method proposed in this article has great potential for real-time embedded applications of HAR.

Modified park transformation of three-phase signals for harmonic extraction with frequency-adaptive capability

To maintain high power quality in a polluted grid with power electronic devices and non-linear loads, the detection and extraction of harmonic components is inevitable, such as for active power filters, regenerative converters, and uninterruptible power supplies. In this paper, the three-phase current/voltage signal is converted to the dq-frame signal with a modification in the angle used for the Park transformation so that with the aid of pre-filtering techniques such as moving average filter and cascaded delayed signal cancellation method, the selected harmonic can be derived easily. With the implementation of the proposed technique, there is no more need for amplitude and phase correction for the extracted harmonic signal previously elaborated in the literature. The proposed scheme is also equipped with a frequency detection technique to be able to follow the frequency variations in the grid. Moreover, some modifications are applied to the detected frequency to restrict the large transients occur when the grid frequency changes suddenly. The simulation tests and results confirm the effectiveness of the proposed schemes.

Adaptive parallel filter method for active cancellation of road noise inside vehicles

Active noise cancellation (ANC) is an efficient and effective method for suppressing low frequency disturbances generated by tyre–road interaction in a vehicle. There are significant differences in road noise inside the vehicle under different driving conditions. However, fixed-filter ANC strategies are unable to achieve superior noise attenuation for different types of noise, and conventional adaptive algorithms require prolonged adaptation which is detrimental to dynamic noise reduction. Thus, this study proposes an adaptive parallel filter method (APFM) that quickly responds to and suppresses varying vehicle interior road noises. The APFM is divided into two phases: the tuning phase and control phase. In the tuning phase, a set of potential noises is adopted to train the corresponding optimal fixed filters. During the control phase, the most appropriate parallel control filter is first selected for each frame based on a selection mechanism to minimise the energy of the estimated error signal. Then, a delayless variable step size normalised frequency-domain block adaptive filter algorithm is adopted to update the selected control filter. In addition, the computational complexity of the proposed APFM is analysed. Numerous simulations and real time in-vehicle experiments conducted using multi-channel ANC headrests have confirmed the feasibility and effectiveness of the proposed algorithm. It is evident that the APFM achieves fast noise reduction response and low steady-state error in attenuating varying in-vehicle road noise, and retains superior performance in the presence of non-pre-trained disturbances.

Low-Scattering X-Band Planar Phased Vivaldi Array Antenna

A low-scattering X-band planar phased Vivaldi array antenna is proposed in this communication. To reduce the scattering cross section (SCS) of the antenna, two types of Vivaldi elements with the defected ground structures (DGSs) are designed, as well as an embedded absorbing array. Under the normal co-polarized (co-pol) incident waves, the reflections of the two Vivaldi elements are close in magnitude but out of phase. Hence, the scattering of the two elements cancels out in the normal direction. Besides, the problem of obvious bistatic SCS peaks, which always arise when utilizing the phase cancellation method to achieve SCS reduction (SCSR), is solved by the interlacing arrangement of the two elements. Under the cross-polarized (cr-pol) incident waves, the incident power is mostly received and absorbed by the absorbing array, which is composed of the dipole elements in the array center and the slot elements on two edges. According to the measured results, the proposed phased Vivaldi array antenna achieves notable cr-pol SCSR over 6–18 GHz, and the average in-band co-pol SCSR reaches 20 dB simultaneously, without any deterioration on the radiation and scanning performances compared to a referenced one.

Digital Self-Interference Cancellation for Full-Duplex UAV Communication System over Time-Varying Channels

Full-duplex unmanned aerial vehicle (UAV) communication systems are characterized by mobility, so the self-interference (SI) channel characteristics change over time constantly. In full-duplex UAV communication systems, the difficulty is to eliminate SI in time-varying channels. In this paper, we propose a pilot-aid digital self-interference cancellation (SIC) method. First, the pilot is inserted into the data sequence uniformly, and the time-varying SI is modeled as a linear non-causal function. Then, the time-varying SI channel is estimated by the discrete prolate spheroidal basis expansion model (BEM). The error of block edge channel estimation is reduced by cross-block interpolation. The result of channel estimation is convolved with the transmitted data to obtain the reconstructed SI, which is subtracted from the received signal to achieve SIC. The simulation results show that the SIC performance of the proposed method outperforms the dichotomous coordinate descent recursive least square (DCD-RLS) and normalized least mean square (NLMS) algorithms. When the interference to noise ratio (INR) is 25 dB, the performance index normalized least mean square (NMSE) is reduced by 5.5 dB and 4 dB compared with DCD-RLS and NLMS algorithms, which can eliminate SI to the noise floor, and the advantage becomes more obvious as the INR increases.

Single‐switch coupled‐inductors‐based high step‐up converter with reduced voltage stress

AbstractThis paper proposes a non‐isolated DC‐DC high step‐up converter. To achieve a high voltage conversion ratio and overcome the problems related to near unity duty‐cycle of the conventional boost converter in high step‐up applications, coupled‐inductors along with switch‐capacitor techniques are merged in this topology. The proposed converter provides continuous input current with low ripple without using any current ripple cancellation method and the voltage across the switch is limited inherently. In order to reduce the control circuit complexity, the proposed converter uses only one switch. These features decrease the complexity of the proposed converter structure. The voltage stress of the semiconductor components is reduced significantly; thus, high‐quality elements (fast power MOSFET switches with low on‐state resistance and Schottky diodes with low forward voltage drop along with low power losses) can be used, which minimizes the switching and conduction losses and improves the converter efficiency. To confirm the converter operation and theoretical analysis, a 200‐W prototype converter with 24‐to‐200‐V input and output voltages operating at 100‐kHz is implemented in the laboratory.

Ambient LoRa Backscatter System With Chirp Interval Modulation

Ambient LoRa backscatter enables battery-free wireless communication with long-range connectivity for the Internet of Things. However, current efforts mainly focus on symbol-level modulation, which trades considerable data rates for long backscatter ranges. To enhance the data rate, this paper presents and prototypes Pacim, which fully explores the potential of long-period LoRa chirps and conveys additional information by varying symbol lengths. Specifically, we propose the chirp interval modulation scheme that modulates multiple data bits in each time interval between two chirp-based anchor symbols. Moreover, we design a twin-chirp cancellation method at the receiver that eliminates the frequency discontinuity within anchor symbols, and propose a fine-grained detection algorithm to measure the arrival time of anchor symbols in the frequency domain. We further propose three reliable methods to improve transmission reliability and analyze the symbol error rate (SER) performance. We also build a hardware prototype and perform comprehensive evaluations. Our experiment results show that Pacim can achieve up to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$8.6 \times $ </tex-math></inline-formula> throughput gain while keeping long-range, compared with the state-of-the-art ambient LoRa backscatter design.

Fully Soft-Switched Non-Isolated High Step-Down DC–DC Converter With Reduced Voltage Stress and Expanding Capability

In this article, a fully soft-switched expandable high step-down dc–dc converter is presented. In order to achieve a high step-down voltage conversion ratio and low component count, the synchronous buck and Cuk converters are integrated. Lower switches’ voltage stress is realized by splitting the input voltage, which can considerably decrease the switches’ conduction loss. Moreover, switching losses along with the reverse recovery problems are mitigated due to the soft-switching operation of all semiconductor devices. The switch utilized for soft-switching operation is also used to replace the output diode as a synchronous rectifier, which reduces the conduction loss. The mentioned features have considerably contributed to the converter efficiency. Furthermore, the converter shares a common ground between the input and the output, which is desirable in many applications, while the converter output current is continuous without adding current ripple cancellation methods. Finally, the number of converter cells can be expanded or reduced; therefore, the converter can be applied to a wide range of loads. The operating principles and analysis of the proposed converter are presented, and the results from the implemented prototype are provided to verify the converter operation and performance.