A novel detection method for warhead fragment targets in optical images under dynamic strong interference environments

A measurement system for the scattering characteristics of warhead fragments based on high-speed imaging systems offers advantages such as simple deployment,flexible maneuverability,and high spatiotemporal resolution,enabling the acquisition of full-process data of the fragment scattering process.However,mismatches between camera frame rates and target velocities can lead to long motion blur tails of high-speed fragment targets,resulting in low signal-to-noise ratios and rendering conventional detection algorithms ineffective in dynamic strong interference testing environments.In this study,we propose a detection framework centered on dynamic strong interference disturbance signal separation and suppression.We introduce a mixture Gaussian model constrained under a joint spatialtemporal-transform domain Dirichlet process,combined with total variation regularization to achieve disturbance signal suppression.Experimental results demonstrate that the proposed disturbance suppression method can be integrated with certain conventional motion target detection tasks,enabling adaptation to real-world data to a certain extent.Moreover,we provide a specific implementation of this process,which achieves a detection rate close to 100%with an approximate 0%false alarm rate in multiple sets of real target field test data.This research effectively advances the development of the field of damage parameter testing.

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.

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.

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：

An Intelligent Optimization Approach to Non-stationary Interference Suppression for Wireless Networks

In this paper, we propose a new technique to effectively suppress non-stationary interference signal for wireless networks. This technique combines a new scheme of interference signal estimation with the intelligent optimization projection. In order to capture interference signal's subspace, a time-varying method is used to estimate the non-stationary interference.Orthogonal polynomials are used for the basis function instead of the power of the time to reduce the computational complexity.The interference is then removed from the corrupted signal by subspace projection, resulting in less distortion to the desired signal. The performance of this approach is validated by computer simulation.

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.

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.

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.

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.

DIFNet:SAR RFI suppression network based on domain invariant features

Synthetic aperture radar(SAR)is a high-resolution two-dimensional imaging radar.However,during the imaging process,SAR is susceptible to intentional and unintentional interference,with radio frequency inter⁃ference(RFI)being the most common type,leading to a severe degradation in image quality.To address the above problem,numerous algorithms have been proposed.Although inpainting networks have achieved excellent results,their generalization is unclear.Whether they still work effectively in cross-sensor experiments needs fur⁃ther verification.Through the time-frequency analysis to interference signals,this work finds that interference holds domain invariant features between different sensors.Therefore,this work reconstructs the loss function and extracts the domain invariant features to improve its generalization.Ultimately,this work proposes a SAR RFI suppression method based on domain invariant features,and embeds the RFI suppression into SAR imaging pro⁃cess.Compared to traditional notch filtering methods,the proposed approach not only removes interference but al⁃so effectively preserves strong scattering targets.Compared to PISNet,our method can extract domain invariant features and hold better generalization ability,and even in the cross-sensor experiments,our method can still achieve excellent results.In cross-sensor experiments,training data and testing data come from different radar platforms with different parameters,so cross-sensor experiments can provide evidence for the generalization.

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.

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.

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.

Self-Interference Elimination by Physical Feedback Channel in CCFD for 3-D Beamforming Communication

The 3-D beamforming scheme has elite as evolving interest because of its efficiency to empower assorted techniques such as vertical and horizontal domains and emanation beamforming according to subscriber's provisions. Usually, 3-D beamforming communication is set up on FDD/TDD approach those effects on the performance of spectrum and energy efficiency. Co-frequency and CoTime Full Duplex(CCFD) is an effective solution to improve the spectrum and energy efficiency by transmitting and receiving simultaneously in frequency and time domain. While, CCFD communication often face the self-interference issue when communication occurs, simultaneously. Consequently, in this paper a self-interference elimination by physical feedback channel in CCFD for 3-D Beamforming communication scheme is proposed to improve the over-all system performance in terms of energy and spectrum efficiency. The simulation and analytical outcomes demonstrated that the proposed system is superior than the traditional one.

Experimental study on siRNA expressing vector-based RNA interference targeting c-Myc in human hepatocellular carcinoma cell line BEL-7402

Objective: To explore the inhibition of the expression of c-Myc in human hepatocellular carcinoma via vector-based RNA interference (RNAi). Methods: Two RNA interference DNA templates targeting c-Myc oncogene were designed via online software and synthesized. By ligation, the fragments were inserted into pSilencer 1.0-U6 to construct the recombinant siRNA expressing plasmids. The identified recombinants were introduced into BEL-7402 cells with Lipofactamine. The inhibition of c-Myc expression, together with the expression of CDK4, hTERT and Gadd45β in c-Myc down-regulated BEL-7402 cells, were analyzed by semi-quantitative RT-PCR. Results: Two recombinant plasmids pSic-myc-1 and pSic-myc-2, which direct the yields of siRNAs targeting c-Myc in cells, were constructed. Among which, pSic-myc-2 was shown to trigger a RNAi-mediated inhibition of expression of c-Myc in BEL-7402 by up to 90%. In c-Myc knockdown BEL-7402 cells, the expression of CDK4 and hTERT were down-regulated with a ratio of 85% and 57%, respectively, while the expression of Gadd45β was up-regulated by up to 110%. Conclusion: The expression of c-Myc in BEL-7402 could be suppressed by vector-based RNA interference successfully. The knockdown of c-Myc in turn resulted in the changes of expression of genes related to cell proliferation and apoptosis. Thus, our study provided a preliminary data in searching of a c-Myc-targeted RNAi therapy of human hepatocellular carcinoma.

基于神经网络的全双工干扰机自干扰对消方法

针对复杂而强的非线性自干扰信号的对消问题,分析全双工系统中发射泄露产生的自干扰信号的组成及其非线性特性,基于多级隔离和对消自干扰的思想,提出一种数字域神经网络方法。神经网络通过快速学习和感知侦收自干扰信道模型参数,能有效地对消泄露进来的自干扰信号。仿真实验结果表明,与传统的线性对消和数字对消方法相比,所提方法能够快速适应雷达信号的变化,具有更强的自干扰抑制能力,为改善全双工干扰机的性能提供了技术途径。

相控阵组网测控同频中继射频自干扰抑制技术

针对相控阵同频中继节点在测控网络系统中自干扰问题,分析收发天线阵列分离情况下的自干扰信号特性。针对接收阵列天线合成后自干扰的特性,提出一种阵射频自干扰抑制方法。该方法根据阵面的布局以及不同规模子阵内自干扰信号的时延扩展,将一定时延扩展范围内的所有阵元等效为一个阵元,从而降低射频干扰抑制的分析复杂度。理论分析和仿真实验结果表明,射频干扰抑制技术在阵列天线中仍然能够实现自干扰抑制,性能与抽头个数强相关,且每个抽头的时延、相位以及幅度的范围选取与子阵划分相关。针对256阵元发射阵面和256阵元接收阵面的场景,仿真对比不同抽头数下的自干扰抑制性能。仿真结果表明,采用16个抽头对载波频率为26.8 GHz,带宽为200 MHz的自干扰信号抑制能力大于47 dB;实际测试结果表明,采用16个抽头进行自干扰射频重建,自干扰抑制能力大于32 dB。