Application of uniform DFT filter bank in radar jamming system

The principle of uniform DFT filter bank is presented. Exploiting poly-phase structure, radar jamming system samples the intercepted wideband radar signals through analysis filter bank by different channels and linearly modulates the intercepted radar signal according to the theory of signal and system, then synthesizes the jamming signal through the synthesis filter hank. The method merely requires lower sample frequency, reduces the computational complexity and the data quantity to be processed. The un-ideal filter＇s influence to the result of signals processing is analyzed by simulating the match filter in radar jamming system.

Modification of polarization filtering technique in HF ground wave radar

The polarization filter using three orthogonal linear polarization antennas can suppress more disturbances than the polarization filter using two orthogonal linear polarization antennas in HF ground wave radar. But the algorithm of the threedimension filter is relatively complicated and not suitable for real-time processing. It can＇t use linear and nonlinear polarization vector translation technique directly. A modified polarization filter which is simple and has same suppressing ability as the three-dimension polarization filter is given. It only has half parameters of the primary one. Some problems about estimation of polarization parameters and selection of disturbances are discussed. A method of holding the phase of radar backscatter signal constantly is put forward so that unstationary disturbance signal can be processed.

Particle filter initialization in non-linear non-Gaussian radar target tracking

When particle filter is applied in radar target tracking, the accuracy of the initial particles greatly effects the results of filtering. For acquiring more accurate initial particles, a new method called “competition strategy algorithm” is presented. In this method, initial measurements give birth to several particle groups around them, regularly. Each of the groups is tested several times, separately, in the beginning periods, and the group that has the most number of efficient particles is selected as the initial particles. For this method, sample initial particles selected are on the basis of several measurements instead of only one first measurement, which surely improves the accuracy of initial particles. The method sacrifices initialization time and computation cost for accuracy of initial particles. Results of simulation show that it greatly improves the accuracy of initial particles, which makes the effect of filtering much better.

Novel matched filtering method and its application in radar system

The method of using a narrowband filter to realize matched filtering is derived.A novel method of using spectrum sampling to realize matched filtering is presented,and the method can conquer the disadvantages that the narrowband filter cannot adopt the adaptive scheduling of phased array radars and realize matched filtering for several waveforms.A novel error extraction method is proposed,which uses a time division multipath method to realize the intermediate frequency extraction.This method can save lots of space for vehicle-born radar systems,reduce the influence of amplitude and phase distortion caused by devices,and enhance the system reliability.Simulation results show that the spectrum sampling method is applicable,and the implementation of frequency spectrum sampling is elaborated.

Time-Expanded Sampling for Ensemble-Based Filters:Assimilation Experiments with Real Radar Observations

By sampling perturbed state vectors from each ensemble prediction run at properly selected time levels in the vicinity of the analysis time, the recently proposed time-expanded sampling approach can enlarge the ensemble size without increasing the number of prediction runs and, hence, can reduce the computational cost of an ensemble-based filter. In this study, this approach is tested for the first time with real radar data from a tornadic thunderstorm. In particular, four assimilation experiments were performed to test the time-expanded sampling method against the conventional ensemble sampling method used by ensemble- based filters. In these experiments, the ensemble square-root filter （EnSRF） was used with 45 ensemble members generated by the time-expanded sampling and conventional sampling from 15 and 45 prediction runs, respectively, and quality-controlled radar data were compressed into super-observations with properly reduced spatial resolutions to improve the EnSRF performances. The results show that the time-expanded sampling approach not only can reduce the computational cost but also can improve the accuracy of the analysis, especially when the ensemble size is severely limited due to computational constraints for real-radar data assimilation. These potential merits are consistent with those previously demonstrated by assimilation experiments with simulated data.

Passive Target Tracking in Non-cooperative Radar System Based on Particle Filtering

We propose a target tracking method based on particle filtering(PF) to solve the nonlinear non-Gaussian target-tracking problem in the bistatic radar systems using external radiation sources. Traditional nonlinear state estimation method is extended Kalman filtering (EKF), which is to do the first level Taylor series extension. It will cause an inaccuracy or even a scatter estimation result on condition that there is either a highly nonlinear target or a large noise square-error. Besides, Kalman filtering is the optimal resolution under a Gaussian noise assumption, and is not suitable to the non-Gaussian condition. PF is a sort of statistic filtering based on Monte Carlo simulation that is using some random samples (particles) to simulate the posterior probability density of system random variables. This method can be used in any nonlinear random system. It can be concluded through simulation that PF can achieve higher accuracy than the traditional EKF.

SPATIAL-TEMPORAL JOINT FILTERP ROCESSING APPROACH FOR PHASED ARRAY AIRBORNE EARLY WARNING RADARS

To suppress the ground clutter for airborne early warning (AEW) radars is the key technique in radar signal processing. In this paper, a spatial-temporal nonadaptive joint filter processing approach is proposed to suppress the clutter for AEW radars, which can significantly reduce the computation compared with other optimal or suboptimal methods. The performance of this approach is better than that of the conventional cascaded nonadaptive processing, especially.

TIME-SPACE 3D MATCHED FILTERING FOR PERFORMANCE ANALYSIS OF SYNTHETIC IMPULSE AND ANTENNA RADAR

The principle and performance of Synthetic Impulse and Antenna Radar(SIAR) are analyzed with the concept of 3D matched filtering. The discussion here is concentrated on the characteristics of SIAR in the case of three dimensions. The results obtained are helpful for designing this new style radar.

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.

RADARSAT图象滤波的研究

在分析 SAR图象斑点噪声特性和主要滤波算法的基础上 ,将中值滤波、均值滤波、LEE与增强 LEE滤波、FROST与增强 FROST滤波、KUAN滤波、GAMMA滤波、小波软阈值滤波等算法应用于 RADARSAT图象滤波 ,以平滑指数和边缘保持指数等作为评价指标 ,对各种方法进行了比较 .结果表明 ,中值、均值滤波算法的效果较差 。

CIC Filter Theory in DDC and Implementation by Using FPGA

Cascade Integrator Comb(CIC) filter is the main part of the next generation High Frequency (HF) radar. This paper describes the key points of CIC theory in the Digital Down Conversion (DDC) module of a radar receiver, and takes advantage of the high flexibility and high density feature of Field Programmable Gate Array (FPGA) for putting forth to design the CIC filter by using FPGA. This paper provides particular insight into design by FPGA, which has advantages in high speed operation and simply structure. Some important and practical applications are given in this paper. The simulation result proves the validity and veracity. Because we can adjust the parameters freely according to our need, the CIC filter can be adapted to the next generation HF radar. Key words FPGA - DDC - CIC filter - HF radar CLC number TN 47 Foundation item: Supported by the 863 High Technology Project of China(2001AA631050)Biography: MA Zhi-gang(1978-), male, Ph. D candidate, research direction: software radio and EDA design.

Doppler radar by using single multicarrier pulse based on optical fibre delay lines

The proposed Doppler measurement technique shows that the Doppler measurements can be accomplished by a single pulse with multiple frequency components through optical fibre delay lines.Range and velocity ambiguity can be removed,and the velocity resolution can be improved dramatically by using long optical fibre delay lines.Furthermore,the velocity resolution can be modified by adjusting the length of optical fibre delay lines.In addition,the proposed radar can achieve high range resolution by using a single wideband pulse.As a result,the new approach can improve radar performance significantly.

Polarimetric whitening filter for POLSAR image based on subspace decomposition

Speckle filtering is an indispensable pre-processing step for applications of polarimetric synthetic aperture radar （POLSAR）, such as terrain classification, target detection, etc. As one of the most typical methods, the polarimetric whitening filter （PWF） can be used to produce a minimum-speckle image by combining the complex elements of the scattering matrix, but polarimetric information is lost after the filtering process. A polarimetric filter based on subspaze decomposition which was proposed by Cu et al specializes in retrieving principle scattering characteristics, but the corresponding mean value of an image after filtering is not kept well. A new filter is proposed for improving the disadvantage based on subspace decomposition. Under the constraint that a weighted combination of the polarimetric SAR images equals to the output of the PWF, the Euclidean distance between an unfiltered parameter vector and a signal space vector is minimized so that noises can be reduced. It is also shown that the proposed method is equivalent to the subspace filter in the case of no constraint. Experimental results with the NASA/JPL airborne polarimetric SAR data demonstrate the effectiveness of the proposed method.

Scheme of adaptive polarization filtering based on Kalman model

A new kind of adaptive polarization filtering algorithm in order to suppress the angle cheating interference for the active guidance radar is presented. The polarization characteristic of the interference is dynamically tracked by using Kalman estimator under variable environments with time. The polarization filter parameters are designed according to the polarization characteristic of the interference, and the polarization filtering is finished in the target cell. The system scheme of adaptive polarization filter is studied and the tracking performance of polarization filter and improvement of angle measurement precision are simulated. The research results demonstrate this technology can effectively suppress the angle cheating interference in guidance radar and is feasible in engineering.

ECCM schemes in netted radar system based ontemporal pulse diversity

For a netted radar system to counteract the deceptionelectronic countermeasure （ECM） signals, an effective electroniccounter countermeasure （ECCM） approach is proposed. The proposedapproach is realized based on the new signaling strategyfor the temporal pulse diversity, which makes use of transmittingpulses at each pulse repetition interval （PRI） with specific transmissionpulse block, and then following proper processing andinformation fusion. The existence of the deceptive ECM signal isconfirmed by one station, while the other stations in the nettedradar with same parameters applied the pulse diversity skillfully.Meanwhile, this method ensured that, pulse diversity can be appliedin netted radar. The performance assessment shows that theproposed solutions are effective in presence of ECM signals. Thisalgorithm has been demonstrated by simulations. The presentedsimulation results are in excellent consensus with theoretical predictions.

Novel polarimetric SAR speckle filtering algorithm based on mean shift

For better interpretation of synthetic aperture radar（SAR） images,the speckle filtering is an important issue.In the area of speckle filtering,the proper averaging of samples with similar scattering characteristics is of great importance.However,existing filtering algorithms are either lack of a similarity judgment of scattering characteristics or using only intensity information for similarity judgment.A novel polarimetric SAR（PolSAR） speckle filtering algorithm based on the mean shift theory is proposed.As polarimetric covariance matrices or coherency matrices form Riemannian manifold,the pixels with similar scattering characteristics gather closely and those with different scattering characteristics separate in this hyperspace.By using the range-spatial joint mean shift theory in Riemannian manifold,the pixels chosen for averaging are ensured to be close not only in scattering characteristics but also in the spatial domain.German Aerospace Center（DLR） L-Band Experiment SAR（E-SAR） data and East China Research Institute of Electronic Engineering（ECRIEE） PolSAR data are used to demonstrate the efficiency of the proposed algorithm.The filtering results of two commonly used speckle filtering algorithms,refined Lee filtering algorithm and intensity driven adaptive neighborhood（IDAN） filtering algorithm,are also presented for the comparison purpose.Experiment results show that the proposed speckle filtering algorithm achieves a good performance in terms of speckle filtering,edge protection as well as polarimetric characteristics preservation.

Multi-baseline extended particle filtering phase unwrapping algorithm based on amended matrix pencil model and quantized path-following strategy

This paper proposes a new multi-baseline extended particle filtering phase unwrapping algorithm which combines an extended particle filter with an amended matrix pencil model and a quantized path-following strategy. The contributions to multibaseline synthetic aperture radar(SAR) interferometry are as follows: a new recursive multi-baseline phase unwrapping model based on an extended particle filter is built, and the amended matrix pencil model is used to acquire phase gradient information with a higher precision and lower computational cost, and the quantized path-following strategy is introduced to guide the proposed phase unwrapping procedure to efficiently unwrap wrapped phase image along the paths routed by a phase derivative variance map.

TWO APPROACHES TO THE DESIGN OF TIME-VARYING CASCADED FILTERS

Two approaches to the design of time-varying cascaded filters used in radar clutter rejection are presented. In the first approach, by fitting the cascaded filter to the noncascaded filter, the time-varying cascaded filter can be designed, which makes it possible that the time-varying cascaded filter behaves just like an optimum clutter filter. The second approach can be used to design the second-stage filter in a time-varying cascaded one by setting zeros in its equivalent overall frequency response. It has been shown that it is difficult to express the frequency response of the second-stage filter in the time-varying cascaded one, however, it is convenient to be involved in the overall response.

Parameterized time-frequency analysis to separate multi-radar signals

Multi-radar signal separation is a critical process in modern reconnaissance systems. However, the complicated battlefield is typically confronted with increasing electronic equipment and complex radar waveforms. The intercepted signal is difficult to separate with conventional parameters because of severe overlapping in both time and frequency domains. On the contrary, time-frequency analysis maps the 1D signal into a 2D time-frequency plane, which provides a better insight into the signal than traditional methods. Particularly, the parameterized time-frequency analysis (PTFA) shows great potential in processing such non stationary signals. Five procedures for the PTFA are proposed to separate the overlapped multi-radar signal, including initiation, instantaneous frequency estimation with PTFA, signal demodulation, signal separation with adaptive filter and signal recovery. The proposed method is verified with both simulated and real signals, which shows good performance in the application on multi-radar signal separation.

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.