Analysis and Compensation of Frequency Offset in Co-Site Adjacent Channel Interference Suppression

Due to the mismatch of the circuit oscillators,there will always be a frequency offset between the transmitter and the receiver.In the adjacent channel interference(ACI)suppression system using the reconstruction and cancellation method,the frequency offset decreases the accuracy of the reconstructed signal and introduces a time-varying term in the interference cancellation,resulting in poor performance of the ACI suppression.In this paper,the relationship between the normalized frequency offset,signal-to-noise ratio and the loss of interference suppression capability is analyzed through formula derivation and simulation.The validity of the frequency offset compensation method based on the pilot sequence is verified,and the relationship between the sequence length and the estimation accuracy is given.This paper provides necessary method reference and data support for the engineering of ACI suppression.

FM interference suppression for PRC-CW radar based on adaptive STFT and time-varying filtering

The influence of frequency modulation （FM） interfer- ence on correlation detection performance of the pseudo random code continuous wave （PRC-CW） radar is analyzed. It is found that the correlation output deteriorates greatly when the FM inter- ference power exceeds the anti-jamming limit of the radar. Accord- ing to the fact that the PRC-CW radar echo is a wideband pseudo random signal occupying the whole TF plane, while the FM in- terference only concentrates in a small portion, a new method is proposed based on adaptive short-time Fourier transform （STFT） and time-varying filtering for FM interference suppression. This method filters the received signal by using a binary mask to excise only the portion of the TF plane corrupted by the interference. Two types of interference, linear FM （LFM） and sinusoidal FM （SFM）, under different signal-to-jamming ratio （S JR） are studied. It is shown that the proposed method can effectively suppress the FM interference and improve the performance of target detection.

An interference suppression algorithm for cognitive bistatic airborne radars

Interference suppression is a challenge for radar researchers, especially when mainlobe and sidelobe interference coexist. We present a comprehensive anti-interference approach based on a cognitive bistatic airborne radar. The risk of interception is reduced by lowering the launch energy of the radar transmitting terminal in the direction of interference;main lobe and sidelobe interferences are suppressed via cooperation between the two radars. The interference received by a single radar is extracted from the overall radar signal using multiple signal classification(MUSIC), and the interference is cross-located using two different azimuthal angles. Neural networks allowing good, non-linear nonparametric approximations are used to predict the location of interference, and this information is then used to preset the transmitting notch antenna to reduce the likelihood of interception. To simultaneously suppress mainlobe and sidelobe interferences, a blocking matrix is used to mask mainlobe interference based on azimuthal information, and an adaptive process is used to suppress sidelobe interference. Mainlobe interference is eliminated using the data received by the two radars. Simulation verifies the performance of the model.

Improved DSE-CMA Error Function for Blind Multiuser Interference Suppression in DS/CDMA Systems

This paper presents an improved error function of dithered signed-error constant modulus algorithm （IDSE-CMA） for blind multiuser interference suppression in DS/CDMA systems. It uses a different error function to replace the former one in sign operation of the DSE-CMA and compares their performance in multiple access interference （MAI） suppression ability. Simulations indicate that the new algorithm has better performance than the similar CMA in terms of convergence speed and steady-state performance：

SUBSET PARALLEL VOLTERRA FILTER FOR NARROWBAND INTERFERENCE SUPPRESSION IN DSSS COMMUNICATIONS

Subset Parallel Adaptive Volterra Filter (SPAVF) design algorithm is proposed in this letter. Contri-bution factor is introduced in SPAVF, and it can get rid of redundant elements efficiently in the extended input vector. Computational weight can be reduced largely, and BER performance of SPAVF can be improved by getting rid of the influence of redundant elements in the input vector. Simulation result proves its advantage compared to AVF and PSVF.

An ISS-OFDM based adaptive filtering mechanism for interference suppression in wireless multi-hop communication network

The negative impact on communication performance in wireless multi-hop communication net-work caused by limited bandwidth,high bit eror rate （BER）,fading,noise and interference is alleviated by an adaptive filtering game based on frequency subbands selection and predetemined threshold.Such threshold is being obtained in Gaussian and multipath fading channel according to the frequency-matching principle and BER performance.The dynamic selection of subbands will obtain high use efficiency without the help of frequency hopping,and propound a new thought to improve band limited communication for wireless multi-hop communication network.The effectiveness of the adaptive filtering method has been verified by interleaving spread spectrum orthogonal frequency division multiplexing （ISS-OFDM） in different interference conditions,and the simulating results based on network simulator 2 （NS2） indicate that system BER can be improved greatly.

A Novel Clutter Suppression Algorithm for Low-Slow-Small Targets Detecting Based on Sparse Adaptive Filtering

Passive detection of low-slow-small(LSS)targets is easily interfered by direct signal and multipath clutter,and the traditional clutter suppression method has the contradiction between step size and convergence rate.In this paper,a frequency domain clutter suppression algorithm based on sparse adaptive filtering is proposed.The pulse compression operation between the error signal and the input reference signal is added to the cost function as a sparsity constraint,and the criterion for filter weight updating is improved to obtain a purer echo signal.At the same time,the step size and penalty factor are brought into the adaptive iteration process,and the input data is used to drive the adaptive changes of parameters such as step size.The proposed algorithm has a small amount of calculation,which improves the robustness to parameters such as step size,reduces the weight error of the filter and has a good clutter suppression performance.

Study on interference suppression based on joint fractional Fourier domain and time domain

An interference suppression algorithm is proposed to meet challenges of the traditional technique in dealing with the linear frequency modulation(LFM) interference,such as high loss of signal-to-noise ratio(SNR),the output signal-to-interfer-ence-plus-noise ratio(SINR) sensitive to input interference-to-signal ratio(ISR) that results in an unstable synchronization,and the spectrum leakage serious in strong ISR situation.This approach firstly makes use of the windowed and lapped technique to the fractional Fourier transform(FRFT) to enhance the ISR improvement and lower the SNR loss.Then by weakening the interference and a secondary threshold process,interference energy can be suppressed as much as possible and the output SINR is less sensitive to the ISR.Finally,a joint fractional Fourier domain and time domain technique is proposed to overcome the residual interference energy caused by the strong interference or the discontinuous-phase interference.Theoretical analysis and simulation results show that the proposed algorithm can achieve better performance than the conventional methods in suppressing both the multi period LFM interference and the multi chirp-rate LFM interference,especially in the strong interference environment.

Performance Analysis of Narrowband Interference Suppression in Orthogonal Code Modulation Spread Spectrum System

This paper analyzes the performance of both in-band and outband narrowband interference suppression in orthogonal code modulation spread spectrum system, and compares with conventional spread spectrum system at the same information transmission rate and spread spectrum bandwidth. Simulation results indicate that the antijamming (narrowband interference) performance obtained from orthogonal code modulation spread spectrum system is much better than that from conventional spread spectrum system.

Principle and simulation of coherent interference suppression by a three-sensor array

The Principles of coherent interference suppression are presented by a three-sensor array. The formulae of extracting expected signals from strong interference are derived. The selection of sensor space is discussed and then relationships between the space and frequency point, at which the signals can be extracted, are given. When expected signals are band- limit, the conditions of the selected sensor space, which should be satisfied, are given. Lastly, Performance of interference suppression is analyzed when the amplitude of interference power spectra of signals Received by three sensors fluctuates, and the expressions of relative error of the extracted signals and processing gain are derived. The theoretical and simulation results show that signals can be extracted from strong background interference without any information about signals and interference expect for the arriving direction of signals, that the space between sensors should be smaller than half wavelength of upper limit freqency when the expected signals are band-limit, and that performance of extracting signals will decline with the increase of fluctuation of interference spectrum amplitude.

Joint adaptive power allocation and interference suppression algorithms based on the MSER criterion for wireless sensor networks

In this study, a two-hop wireless sensor network with multiple relay nodes is considered where the amplify-and-forward(AF) scheme is employed. Two algorithms are presented to jointly consider interference suppression and power allocation(PA) based on the minimization of the symbol error rate(SER) criterion. A stochastic gradient(SG) algorithm is developed on the basis of the minimum-SER(MSER) criterion to jointly update the parameter vectors that allocate the power levels among the relay sensors subject to a total power constraint and the linear receiver. In addition, a conjugate gradient(CG) algorithm is developed on the basis of the SER criterion. A centralized algorithm is designed at the fusion center. Destination nodes transmit the quantized information of the PA vector to the relay nodes through a limited-feedback channel. The complexity and convergence analysis of the proposed algorithms are carried out. Simulation results show that the proposed two adaptive algorithms significantly outperform the other previously reported algorithms.

Interference suppression for ultra dense network based on compressive sensing framework

Ultra-dense network(UDN)deployment of small cells introduces novel technical challenges,one of which is that the interference levels increase considerably with the network density.This paper proposes interference suppression scheme based on compressive sensing(CS)framework for UDN.Firstly,the measurement matrix is designed by exploiting the sparsity of millimeter wave channels.CS technique is employed to transform the high dimension sparse signal into low dimension signal.Then,the interference is canceled in the compressed domain.Finally,the stagewise weak orthogonal matching pursuit(SWOMP)algorithm is used to reconstruct the useful signal after interference suppression.The analysis and simulation results demonstrate the effectiveness of the algorithm.Simulation results demonstrate that the proposed interference suppression in compressive domain yields performance gains compared to other classical interference suppression schemes.The proposed algorithm can reduce the computational complexity of interference suppression algorithm.

Code-aided Interference Suppression in Direct Sequence Spread Spectrum Systems with Eigenvector Sign Spreading Code

For direct sequence spread spectrum (DSSS) communication systems suffering interference, it is known that code-aided interference suppression technique outperforms all of the previous linear or nonlinear methods. In this paper, we proposed an improved code-aided technique which can improve the system performance greatly by using the eigenvector sign (EVS) spreading sequence which depends on the statistical characteristics of the interference and the thermal noise.

Suppression to the cross-channel interference based on the short time Fourier transform

A new cross-channel interference suppression method is proposed to decrease the cross-channel interference in beat signals based on the short time Fourier transform （STY3＂） and the inverse short time Fourier transform （ISTFT） when the dual-orthogonal polarimetric frequency-modulated continu- ous wave （FMCW） radar adopts the opposite-slope linear frequency modulation signal pair in the simultaneous measurement mode. The STFT is applied only on the signals in the cross-interference intervals in the four polarimetric channels to decrease the computation complexity. A mask matrix for suppressing the interference is constructed using the constant false alarm ratio （CFAR） detection on the spectrograms by the STFY. The simulative results show that the cross-channel interference is effi- ciently suppressed by the proposed method. The comparison between the proposed method and the rejection method verifies the improved performance of the proposed method.

Multiple interferences suppression with space-polarization null-decoupling for polarimetric array

The adaptive digital beamforming technique in the space-polarization domain suppresses the interference with forming the coupling nulls of space and polarization domain.When there is the interference in mainlobe,it will cause serious mainlobe distortion,that the target detection suffers from.To overcome this problem and make radar cope with the complex multiple interferences scenarios,we propose a multiple mainlobe and/or sidelobe interferences suppression method for dual polarization array radar.Specifically,the proposed method consists of a signal preprocessing based on the proposed angle estimation with degree of polarization(DoP),and a filtering criterion based on the proposed linear constraint.The signal preprocessing provides the accurate estimated parameters of the interference,which contributes to the criterion for null-decoupling in the space-polarization domain of mainlobe.The proposed method can reduce the mainlobe distortion in the space-polarization domain while suppressing the multiple mainlobe and/or sidelobe interferences.The effectiveness of the proposed method is verified by simulations.

Narrow-band interference excision in spread-spectrum systems using new N-sigma algorithm based on fuzzy threshold

The key to narrow-band interference excision in frequency domain is to determine the excision thresh- old in direct-sequence spread-spectrum （DS-SS） systems. The excision threshold is a non-linear function related to the number and the power of interference, and attempting to get the exact relation of threshold related to the number and the power of interference is almost impossible. The N-sigma algorithm determines the excision threshold using subsection function; however, the excision threshold determined by this method is not exact. A new method to determine the threshold of N-sigma algorithm is proposed. The new method modifies the scale factor N by use of the membership function. The threshold determined by this method is consecutive and smooth, and it is closer to the fact than that of the initial N-sigma algorithm. The GPS signal and single-tone （CW） interference （that is, typical narrow-band interference） are implemented in the simulation, and the results are presented to demonstrate the validity of the new algorithm.

Independent Component Analysis Based Blind Adaptive Interference Reduction and Symbol Recovery for OFDM Systems

To overcome the inter-carrier interference （ICI） of orthogonal frequency division multiplexing （OFDM） systems subject to unknown carrier frequency offset （CFO） and multipath, this paper develops a blind adaptive interference suppression scheme based on independent component analysis （ICA）. Taking into account statistical independence of subcarriers＇ signals of OFDM, the signal recovery mechanism is investigated to achieve the goal of blind equalization. The received OFDM signals can be considered as the mixed observation signals. The effect of CFO and multipath corresponds to the mixing matrix in the problem of blind source separation （BSS） framework. In this paper, the ICA- based OFDM system model is built, and the proposed ICA-based detector is exploited to extract source signals from the observation of a received mixture based on the assumption of statistical independence between the sources. The blind separation technique can increase spectral efficiency and provide robustness performance against erroneous parameter estimation problem. Theoretical analysis and simulation results show that compared with the conventional pilot-based scheme, the improved performance of OFDM systems is obtained by the proposed ICA-based detection technique.

Radio Disturbance Suppression for Ground Wave Radar

A new method of single sample polarization filtering is proposed. The algorithm is fast and suitable for the polarization processing of stationary or nonstationary polarized disturbed signals with one or more independent disturbances. A ground wave polarimetric radar with the ability of radio disturbance suppression is then introduced. Some numerical results demonstrate the effectiveness of single sample polarization filtering method for ground wave polarimetric radar.

UWB SAR RFI SUPPRESSION BASED ON REGION OF SUPPORT IN 2-D WAVENUMBER DOMAIN

Radio Frequency Interference (RFI) degrades the quality of focused Ultra-WideBand Syn- thetic Aperture Radar (UWB SAR) images. From both the theoretical analysis and real data valida- tion, it is concluded that target echo and RFI have different Region Of Support (ROS) in 2-D fast- time wavenumber and aperture wavenumber domain. Consequently, a novel adaptive filter is pro- posed according to the Wiener optimum criterion on the distinct ROS characteristics of target echo and RFI. Compared with the notch filter and the Least Mean Square (LMS) adaptive filter in previ- ous literatures, the proposed method is more computationally efficient with satisfactory suppression results. In terms of Signal-to-Interference Ratio Improvement (SIRI) and processing time, the per- formance of the proposed adaptive filter is verified with the field data collected with a UWB SAR system.

Target detection using CDMA based passive bistatic radar

Recently, the code division multiple access （CDMA） waveform exists in the large area across the world. However, when using the CDMA system as the illuminator of opportunity for the passive bistatic radar （PBR）, there exists interference not only from the base station used as the illuminator of opportunity but also from other base stations with the same frequency. And be cause in the CDMA system, the signal transmitted by each base station is different, using the direct signal of one base station can not cancel the interference from other base stations. A CDMA based PBR using an element linear array antenna as both the reference antenna and surveillance antenna is introduced. To deal with the interference in this PBR system, an adaptive temporal cancellation algorithm is used to remove the interference from the base station used as the illuminator of opportunity firstly. And then a robust adaptive beamformer is used to suppress the interference from other base stations. Finally, the preliminary experiment re sults demonstrate the feasibility of using CDMA signals as a radar waveform.