Clutter Spectrum Research Articles

Sparsity‐based space–time adaptive processing using complex‐valued Homotopy technique for airborne radar

In this study, a novel sparsity-based space–time adaptive processing algorithm based on the complex-valued Homotopy technique is proposed for airborne radar applications. The proposed algorithm firstly extends the existing standard real-valued Homotopy method to a more general complex-valued application using the gradient approaches. By exploiting the sparsity of the clutter spectrum in the whole spatiotemporal plane, the proposed algorithm recovers the clutter spectrum via the proposed complex Homotopy algorithm and then uses it to estimate the clutter covariance matrix, followed by the space–time filtering and the target detection. Furthermore, the implementations of the proposed algorithm are detailed. The computational complexity analysis shows that the proposed algorithm has a lower-computational complexity than the existing complex-valued Homotopy algorithm. Simulation results show that the proposed algorithm converges at a very fast speed (only 4–6 snapshots in the authors simulations) and provides both excellent detection performance and easy parameter settings.

Transient interference excision and spectrum reconstruction with partial samples for over‐the‐horizon radar

For target detection with sparsely sampled over-the-horizon radar (OTHR) signal, there are two major hassles puzzling its clutter and target Doppler spectrum reconstruction. On one hand, the OTHR signal is usually contaminated by transient interferences, which usually leads to a significant signal loss in its excision with conventional methods. On the other hand, the sparse OTHR signal will introduce serious grating-lobes in conventional Doppler analysis methods and thus degrade the performance of target detection. In this study, an integrate clutter and target spectrum reconstruction method for sparse OTHR signal are proposed. The proposed method contains two aspects. First, based on the sparse basis representation, a transient interference excision method is developed, which uses time-frequency modulated rectangle window basis to represent the OTHR signal in a sparse way to identify transient interferences. The second aspect lies in that, based on the compressive sensing, a spectrum reconstruction method is proposed to obtain the integrate clutter and target spectrum with sparse samples. By solving the Doppler sparsity constrained optimisation with greedy algorithms, the complete Doppler spectrum is recovered effectively for target detection. The performance of the authors proposal is validated by both simulation and real-measured data sets.

Characteristics of the DC/AC Ratio of Radar Backscatter from Trees

In the analysis of fluctuating clutter in radar systems, the dc/ac ratio, defined as the ratio of power contained in the dc component at zero Doppler to the power contained in the clutter spectrum, is an important parameter which impacts the detection of slowly-moving targets. Thus, proper characterization of the dc/ac ratio is important for a meaningful assessment of system performance. We explain why the dc component can be hidden due to shortness of the data set or due to apodization. We show that a random propagation time can explain any form of dc/ac ratio and many shapes of the broadband Doppler spectra. Examples are based on a paper by Narayanan et al. about backscatter from trees of a radar at 8 GHz.

Range ambiguity clutter suppression for bistatic STAP radar

Bistatic pulse-Doppler airborne radar has desirable properties such as the low probability of detection by other radars relative to its monostatic counterpart. However, the clutter characteristics of bistatic airborne radar are more complex than those of monostatic airborne radar. The clutter spectra not only vary severely with range, but also vary with bistatic configuration. In this article, the geometry model of bistatic airborne radar is given, and the approximate estimation expressions for clutter degrees of freedom (DOFs) are presented. Then a novel clutter suppression method for bistatic airborne radar with range ambiguity is presented. The method completes registration-based range ambiguity clutter compensation based on non-uniform sampling and the estimated clutter DOFs. The simulation results illustrate the performance improvement achieved for bistatic airborne radar.

An Improved Clutter Suppression Method for Non-Sidelooking Uniform Linear Array Antennas Airborne Radar

The clutter distribution of airborne radar with non-sidelooking uniform linear array antennas varies with ranges and samples in different range gates are not independent identically distributed vectors, so that the statistical STAP methods degrade greatly. In this paper, an improved clutter range dependence compensation method for airborne radar with uniform linear array is proposed. This method involves in a preprocessing with ADC method to align the mainlobe of clutter spectrum in different range gates and subsequently clutter suppression in other azimuths with EDBU technology. Simulation results show the proposed method can reduce the clutter spectrum dispersion significantly and outperform conventional local compensation methods.

Two-dimensional pulse-to-pulse canceller applied in multiple-input–multiple-output radar

Since the spectrum of the ground clutter in the ground-based pulse radar is spatially–temporally decoupled, a simple pulse-to-pulse canceller is often used as a moving target indication filter for suppressing the ground clutter near the zero-Doppler frequency. In contrast, in the airborne phased-array radar, which is a typical single-input–multiple-output radar, the spectrum of the ground clutter is spatially–temporally coupled each other, and the two-dimensional pulse-to-pulse canceller (TDPC) for ground clutter cancellation has been developed by using the ground clutter model in the spatial–temporal domain. Based on the ground clutter model of multiple-input–multiple-output (MIMO) radar, the authors can extend the existing TDPC to more general form that can suppress the ground clutter in the MIMO radar. As the MIMO TDPC can be calculated offline by utilising the geometry knowledge of the ground clutter of MIMO radar, it can be used as an efficient and convenient ground clutter pre-filtering tool.

Ionospheric decontamination for skywave OTH radar based on complex energy detector

For over-the-horizon (OTH) radar, the ocean clutter is very strong. And this becomes a big challenge for the target detection. The clutter suppression is a very important procedure for the OTH radar. For the skywave OTH radar, the radar signal will propagate through the ionosphere. This will cause a contamination due to its unstable movement. Then the Bragg frequencies will be smeared and clutter spectrum will spread wider rather than a single line spectra. This smear will cause the target more difficult to be detected and even buried in clutter. Compensation is necessary to cancel the ionospheric effect. This article proposes the clutter decontamination algorithm based on the complex energy detector (CED). The energy detector (ED) is originally proposed to demodulate the real AM–FM signals. The ED is expanded to complex domain. After the expansion, there is no mutual coupling between the amplitude and frequency component for an AM–FM signal. The phase of the Bragg clutter return contaminated by the ionosphere is modeled by a frequency-modulated signal, while its magnitude is amplitude modulated. The CED algorithm is applied to track the instantaneous frequency of the contaminated return signal, which is then used for compensation. Simulation results are presented. The simulation results show that, comparing with the Hankel rank reduction algorithm, the proposed algorithm has better performance under the situation of large frequency fluctuation.

Signal decomposition of HF radar maneuvering targets by using S<sup>2</sup>-method with clutter rejection

Multiple maneuvering targets signal processing in high frequency radar is challenging due to the following difficulties: the interference between signals is severe because of significant spread of the target Doppler spectrum, the low signal to clutter ratio (SCR) environment degrades the performance of signal processing algorithms. This paper addresses this challenging problem by using an S 2 -method and an adaptive clutter rejection scheme. The proposed S 2 -method improves the S-method by eliminating interference between signals, and thus it enables multi-target signals to be reconstructed individually. The proposed adaptive clutter rejection scheme is based on an adaptive notch filter, which is designed according to the envelop of the clutter spectrum. Experiments with simulated targets added into radar sea clutter echo and real air target data illustrate the effectiveness of the proposed method.

Low Wave Number Radar Image Energy Influence on Determining Current

In the radar imaging mechanism different phenomena are present, as a result the radar image is not a direct representation of the sea state. In analyzing radar image spectra, it can be realized that all of these phenomena produce distortions in the wave spectrum. The main effects are more energy for very low frequencies. This work investigates the structure of the sea clutter spectrum, and analysis the low wave number energy influence on determining sea surface current. Then the radar measure current is validated by experiments. By comparing with the in situ data, we know that the radar results reversed by image spectrum without low wave number spectrum have high precision. The low wave number energy influent determining current seriously.

Pre-Compensation Clutter Range-Dependence STAP Algorithm for Forward-Looking Airborne Radar Utilizing Knowledge-Aided Subspace Projection

The range-dependence of clutter spectrum for forward-looking airborne radar strongly affects the accuracy of the estimation of clutter covariance matrix at the range under test, which results in poor clutter suppression performance if the conventional space-time adaptive processing (STAP) algorithms were applied, especially in the short range cells. Therefore, a new STAP algorithm with clutter spectrum compensation by utilizing knowledge-aided subspace projection is proposed to suppress clutter for forward-looking airborne radar in this paper. In the proposed method, the clutter covariance matrix of the range under test is firstly constructed based on the prior knowledge of antenna array configuration, and then by decomposing the corresponding space-time covariance matrix to calculate the clutter subspace projection matrix which is applied to transform the secondary range samples so that the compensation of clutter spectrum for forward-looking airborne radar is accomplished. After that the conventional STAP algorithm can be applied to suppress clutter in the range under test. The proposed method is compared with the sample matrix inversion (SMI) and the Doppler Warping (DW) methods. The simulation results show that the proposed STAP method can effectively compensate the clutter spectrum and mitigate the range-dependence significantly.

Fractal characteristic in frequency domain for target detection within sea clutter

This study mainly describes the fractal property of the frequency spectrum of the sea clutter and the application of the obtained fractal characteristic in frequency domain to the constant-false-alarm-rate (CFAR) target detection within sea clutter. First, this study takes fractional Brownian motion (FBM) for example, and the spectrum of the FBM is proved to be fractal theoretically on condition that the time series of the FBM is fractal. This argument lays the foundation for the application of fractal theory to the frequency spectrum. Next, X - and S -band real radar data are used for the verification of the fractal property of the real sea clutter frequency spectrum. Finally, the effects of the length of the time series and fast Fourier transform (FFT) are analysed in detail. The results show that the frequency spectrum of the real sea clutter is fractal in the statistical sense and the frequency Hurst exponents of clutter range bins and target range bins are distinguishable. Therefore the frequency Hurst exponent is used for the CFAR target detection within sea clutter.

ADAPTIVE CLUTTER SUPPRESSION FOR AIRBORNE RANDOM PULSE REPETITION INTERVAL RADAR BASED ON COMPRESSED SENSING

We present an adaptive clutter suppression method for airborne random pulse repetition interval radar by using prior knowledge of clutter boundary in Doppler spectrum. In this method, by exploiting the intrinsic sparsity, compressed sensing based on iterative grid optimization (CS-IGO) is applied to directly recover the clutter spectrum with only the test range cell instead of nonhomogeneous training data from adjacent range cells. Since the sensing matrix and clutter spectrum obtained by CS-IGO are well adapted to the data, the prewhitening fllter can be efiectively obtained to cancel the mainlobe clutter. Further, the clutter residue can be suppressed by the iterative reweighted l1 minimization to enhance the target response. Simulation results show that the approach is capable of efiective suppression of clutter and precise recovery of targets' unambiguous spectrum, ofiering a high performance of output signal to clutter and noise ratio.

Space-time Separated Interpretation Method for Forward-looking Airborne Radar Clutter Spectrum

在机载前视阵雷达中，由于杂波距离相关性的存在，导致待检测距离单元杂波的协方差矩阵估计存在偏差，致使空时自适应处理(STAP)的杂波抑制性能下降。空时插值法是一种内插变换方法，能够有效降低机载前视阵雷达杂波的杂波距离相关性，然而该方法计算量非常大，给它的实时处理带来困难。该文提出一种空时分离的插值方法，该方法将空时插值方法在空域和时域分别独立实现。与空时插值方法相比，该方法能够在性能损失不大的情况下，极大地降低计算量，并且当存在阵元误差时，该方法也能获得好的处理性能。计算机仿真结果验证了该方法的有效性。

표적 도플러 속도와 클러터 스펙트럼 특성에 따른 레이더 신호 처리기의 탐지 성능 분석

MTI filter is used to separate target signal from clutter in many radar signal processing. By suppressing clutter before CFAR detection, the detection performance can be improved. As a radar system designed, a design engineer generally takes averaged SNR and CNR into account and does not include the effect of MTI filter`s frequency response. In practice, when the signals including clutter are pass through the filter, SNR is widely varying according to target velocity and CNR is also varying according to clutter center frequency and spectrum spreading. In this paper, we have derived the relationship between the MTI filter`s frequency response and a target`s velocity and a clutter`s spectrum characteristics. With the variation of SNR and CNR at the filter output, the detection performance of CFAR has been analyzed by the simulation and has made certain of their influences on the performance.

PCA-Based Detection Algorithm of Moving Target Buried in Clutter in Doppler Frequency Domain

This letter proposes a novel technique for detecting a target signal buried in clutter using principal component analysis (PCA) for pulse-Doppler radar systems. The conventional detection algorithm is based on the fast Fourier transform-constant false alarm rate (FFT-CFAR) approaches. However, the detection task becomes extremely difficult when the Doppler spectrum of the target is completely buried in the spectrum of clutter. To enhance the detection probability in the above situations, the proposed method employs the PCA algorithm, which decomposes the target and clutter signals into uncorrelated components. The performances of the proposed method and the conventional FFT-CFAR based detection method are evaluated in terms of the receiver operating characteristics (ROC) for various signal-to-clutter ratio (SCR) cases. The results of numerical simulations show that the proposed method significantly enhances the detection probability compared with that obtained using the conventional FFT-CFAR method, especially for lower SCR situations.

Target detection in high-resolution sea clutter via block-adaptive clutter suppression

Attentions have been focused on the moving target detection in a high-resolution sea clutter. This study commences with a proposal of median-based estimator to estimate the power spectrum of high-resolution sea clutter by the time series observed in adjacent range cells and time intervals. The estimator provides a robust estimation when just a few aberrant time series happen in observation. Based on the estimator, a block-adaptive clutter suppression filter (BACSF) is designed to suppress the clutter prior to the pulse integration. Then, the residual clutter, the output of the BACSF, is modelled as spherically invariant random vector. Upon applying an adaptive normalised matched filter (ANMF) to the residual clutter, a residual clutter's ANMF detector is derived. Moreover, in high-resolution radar background, considering that the approximately stationary intervals of sea clutter and residual clutter are much shorter than the coherent processing interval, another heuristic block-ANMF detector is proposed. It can integrate more pulses and can achieve better performance than the ANMF detector does. This study concludes with the experiments of simulated target against the real sea clutter. The experimental results demonstrate that, when target's Doppler frequency is beyond strong clutter region, the ANMF detector and block-ANMF detector perform better in the residual clutter than in the clutter.

Velocity ambiguity resolving for moving target indication by compressed sensing

A novel velocity ambiguity resolving method is proposed for moving target indication, in which compressed sensing (CS) is applied to recover the unambiguous Doppler spectrum of targets from randomly pulse repetition frequency-jittering pulses. Weighting in CS recovery is utilised to suppress the clutter by using prior knowledge of the clutter spectrum. Experimental results demonstrate the effectiveness of the proposal.

Super-resolution techniques for wind turbine clutter spectrum enhancement in meteorological radars

The Doppler resolution for wind turbine clutter (WTC) returns usually gets degraded when using the operational standard scanning mode of meteorological radars. Here, the use of super-resolution techniques for improving the Doppler resolution is proposed. This study concentrates on the spectral estimation based on auto-regressive coefficients and the multiple signal classification algorithm. The former usually brings to light the four components of WTC, that is, the tower and the three blades, hence outperforming the classical Fourier spectral estimation. The latter, on the contrary, may be improper for scenarios with weather returns. To derive the pertinent conclusions, both classical spectral estimation and the commented super-resolution approaches are applied to simulated and real data coming from both WTC and weather.

Study on detection and recognition of phase contamination and multimode propagation in ionosphere for OTHR

Recognition of ionosphere phase contamination and multimode propagation is an important step in rejection of clutter spectrum spread for OTHR. Based on the algorithm of time reversibility, this paper proposes a method based on eigenvalue decomposition to detect multimode propagation. Besides, a cascaded technique composed of the two methods above is proposed to recognise contaminations. Another detection algorithm based on time series Hankel matrix is proposed, which will be suitable for more widely application. For the first time, the method based on backscatter sounding is also proposed for multimode recognition, and a hybrid method based on time reversibility and Hankel matrix is also proposed to distinguish phase contamination and multimode propagation.

Physical modeling and spectrum spread analysis of surface clutter in forward scattering radar

In this paper, based on the processing results of measured clutter data in forward scattering radar, a special phenomenon that the clutter spectrum spread is insensitive to the wind speed and carrier frequency is observed. The pendulum model is first time introduced into the physical modeling and formation mechanism analysis of surface clutter, and the quantitative expression of clutter spectrum spread is analytically obtained. Under the assumption of pendulum model, the processing results of measured clutter data agree well with the results of theoretical analysis, which fully verifies the correctness of pendulum model and reveals the formation mechanism of surface clutter spectrum in forward scattering radar. Furthermore, according to the stability of clutter spectrum spread with respect to carrier frequencies and wind speed, the optimal cutoff frequencies of clutter filter can be obtained, which establishes the basis for moving target detection and accurate parameters estimation.