Clutter Suppression Algorithm Research Articles

Elevation Adaptive Algorithm for Short-Range Clutter Suppression in Airborne Phased Array Radar

Elevation Adaptive Algorithm for Short-Range Clutter Suppression in Airborne Phased Array Radar

SUBSPACE IMPULSIVE INTERFERENCE SUPPRESSION IN OTHR

This paper proposes a novel subspace projection algorithm for impulsive interference (IMI) suppression in echo samples received by an over-the-horizon radar (OTHR). We particularly highlight the model that the frequency spectrum of IMI component is a complex cosine signal such that IMI cosine can be filtered out by subspace projection. Compared with existing algorithms, a more simple clutter suppression algorithm is used to reject the most powerful clutter components. Furthermore, this algorithm will neither estimate nor need the exact temporal position of IMI, which avoids the impact resulted from the position estimation error. Another advantage is its little impact on true target signal and no impact on the clutter. Experimental results based on data from real high frequency surface wave (HFSW) OTHR systems are also shown to verify the proposed algorithm.

Adaptive spatial-temporal filtering methods for clutter removal and target tracking

In space-based infrared (IR) ballistic missile defense sensor systems, cluttered backgrounds are typically much more intense than the equivalent sensor noise or the targets being detected. Therefore, the development of efficient clutter removal and target preservation/enhancement algorithms is of crucial importance. To meet customer requirements, the advanced clutter rejection algorithms should provide more than 20 dB improvement in detection sensitivity. We propose an adaptive parametric spatial-temporal filtering technique together with the jitter compensation (scene stabilization). The results of simulations and processing of real data show that the developed adaptive spatial-temporal clutter suppression (CLS) algorithms allow for efficient clutter rejection in all tested situations. Proposed algorithms completely remove heavy clutter in the presence of substantial jitter and do not require expensive subpixel jitter stabilizers. In contrast, spatial-only filters and temporal differencing methods can be used only for weak and relatively correlated clutter. A stand-alone simulator was developed to demonstrate capabilities and performance of various algorithmic approaches. Simulations model various geometries, resolutions, illuminations, and meteorological conditions for space-based IR staring sensor systems.

Advanced intermittent clutter filtering for radar wind profiler: signal separation through a Gabor frame expansion and its statistics

Abstract. A new signal processing method is presented for the suppression of intermittent clutter echoes in radar wind profilers. This clutter type is a significant problem during the seasonal bird migration and often results in large discrepancies between profiler wind measurements and independent reference data. The technique presented makes use of a discrete Gabor frame expansion of the coherently averaged time series data in combination with a statistical filtering approach to exploit the different signal characteristics between signal and clutter. The rationale of this algorithm is outlined and the mathematical methods used are presented in due detail. A first test using data obtained with an operational 482 MHz wind profiler indicates that the method outperforms the previously used clutter suppression algorithm.

A Novel Clutter Suppression Algorithm for Landmine Detection With GPR

In this paper, we propose a new algorithm for the enhancement of plastic-cased antipersonnel mine detection using a video-impulse ground-penetrating radar (GPR). The algorithm is implemented as a nonlinear signal processor, which searches for the presence of a reference waveform in a 1D GPR echo return. The reference waveform represents a class of targets within a certain environment. The processor marks the presence of all responses similar to the reference waveform with a sharp mono-cycle. Simultaneously, responses with different waveforms, which presumably correspond to clutter, are suppressed. The reference waveform and other algorithm parameters are determined from training data sets acquired in a controlled environment. After training, the algorithm can be successfully applied at sites where soil, targets, and measurement scenarios are similar but not identical to those of the training site. The processor is integrated into an automated data processing and mine detection scheme as an additional clutter suppression step. The scheme consists of clutter suppression, synthetic aperture radar focusing, construction of a confidence map, and automated detection in it. The suggested algorithm is tested on experimental data, and its performance is compared against schemes where clutter suppression is organized by means of background removal and the cross correlation with a reference wavelet. The performance comparison is done in terms of receiver operating characteristic curves. It has been found that the suggested algorithm reduces the false alarm rate in about two and a half times in comparison to the cross-correlation-based clutter suppression.

Efficient particle filter-based processing algorithm for clutter suppression and IR point targets enhancement

A novel soft decision-based median subtraction filter is presented for clutter suppression and infrared (IR) point targets enhancement. The decision is made based on a jump Markov model and its state and parameter estimation using a particle filter. The scheme is compared with other conventional clutter background removal techniques and good results are obtained.

Adaptive ionospheric clutter suppression based on subarrays in monostatic HF surface wave radar

Coherent sidelobe cancellation (CSLC) based on subarrays has emerged as a key technology for improving the performance of radar systems required to operate in the presence of severe interference which generally includes clutter as well as jamming. While the theory of CSLC is well known, practical issues such as how to set up the subarrays and how to avoid diminishing the desired signal when the clutter is rejected need to be addressed when it comes to implementing CSLC in operational radar systems. A new adaptive ionospheric clutter suppression algorithm based on subarrays for monostatic HF surface wave radar (HFSWR) is introduced and analysed. Detailed comparisons between the proposed algorithm and conventional CSLC are performed. Simulation and real data results confirm that the general and robust algorithm can achieve effective ionospheric clutter suppression, while not decreasing the strength of the first-order sea echo using the data recorded by the OSMAR2003 (Ocean State Monitor and Analysis Radar, manufactured in 2003), located near Zhoushan in Zhejiang, China.

Statistics of Simulated Ocean Clutter

The statistical description of ocean clutter, which is made use of by the modern clutter suppression algorithms, is examined for sea states 0 and 4, for a grazing angle range 0.14° gr 89.5° , for all polarizations, and for upwind and crosswind returns. The data for statistical description are obtained by a radar simulation program in which the electromagnetic pulses are traced in a user defined radar environment. In this simulation environment, the returns which are backscattered from the ocean surface are recorded individually along with their polarization, amplitude, phase, arrival time and Doppler shift. Based on the likelihood ratios of commonly used Rayleigh, Lognormal, Weibull and K-distribution families, the best fitting distributions to the observed data are chosen. When the results obtained are compared with those available in the literature, a good agreement is observed. Due to the limitations of experimental studies, the data necessary for the statistical description of the amplitude and the power of clutter are either not available or scarce for various sea states, grazing angles, polarizations and wind directions. For those cases where the statistical description is not available in the literature, the simulation program provides an inexpensive and reliable environment to obtain the best fitting distributions, which is an important ingredient of the modern clutter suppression algorithms.

A methodology for modeling and simulation of radar clutter and multipath

A computer program is developed to simulate the propagation of a radar pulse for a defined radar scenario. The program traces the electromagnetic wave in time in the radar background. The returns from various paths and the target can be individually recorded along with time delay and Doppler shift information. The program is modular so desired radar, target and earth surface models can be inserted to realize the desired radar scenarios. The returns can be individually processed and the characteristics of target, multipath and clutter can be investigated in time and frequency even for scenarios which are difficult to be realized experimentally. The effects of various radar, target and background parameters can be obtained so more reliable models of clutter and multipath can be developed. These models are extremely useful in the test and development of target detection and clutter suppression algorithms. The operation of the simulation program is tested by implementing a concrete radar scenario, which consists of a monostatic X-band radar searching for a low altitude target over the ocean surface. The results for the sea surface backscatter normalized radar cross section with respect to arrival time, wind direction, polarization, sea state and grazing angle are presented and compared with the available data in the literature and very good agreement is observed. The multipath data in time are obtained for two different target orientations and compared with each other. The radar simulation program proved itself to be a versatile tool to generate radar scenarios on the computer and obtain reliable synthetic data for clutter and multipath which can be used for more successful signal processing algorithms for target detection and clutter suppression.

SAR clutter suppression using probability density skewness

A clutter suppression algorithm is described which exploits asymmetry in the probability density function (pdf) of ground clutter in synthetic-aperture radar (SAR) imagery. In the log-magnitude domain, the probability densities of returns from natural ground clutter and man-made objects exhibit opposite skewness. Using Pearson's second coefficient of skewness, we have observed negative skewness values for natural clutter regions and positive skewness values for buildings and simulated ground vehicles. Clutter suppression is achieved by attenuating regions having negative skewness relative to regions having positive skewness. Using this approach we have obtained a 9 dB increase in target-to-clutter ratios in SAR images of rural scenes with buildings and other scenes with simulated ground vehicles embedded at various locations. We have also applied the skewness metric to the problem of segmenting man-made objects from clutter backgrounds. Here a slightly modified version of Pearson's second coefficient of skewness is used as a test statistic analogous to that of an ordered statistic (OS) constant false alarm rate (CFAR) algorithm. Segmentation of simulated ground vehicles embedded in natural ground clutter is demonstrated using the skewness test statistic. >

Analysis of a non-linear frequency diverse clutter suppression algorithm

The target signal is often received in the presence of coherent noise resulting from a large number of complex and randomly distributed scatterers known as clutter, whose echoes can suppress or mask the actual target echo. This is a fundamental limitation which exists in all imaging and detection applications and cannot be removed by conventional techniques, such as time averaging. This paper examines a non-linear signal processing algorithm (polarity thresholding) used in conjunction with a frequency diversity technique (split-spectrum processing), which decorrelates clutter. Since the target echo exhibits significantly smaller amplitude variations with frequency compared to clutter, the polarity thresholding algorithm can achieve flaw enhancement by setting the output to zero at time instants where phase reversal occurs. Theoretical derivations are provided to determine the signal to noise ratio enhancement capabilities of the algorithm. Ultrasonic data obtained from large grained stainless-steel samples with flat-bottom holes are used to verify the theoretical results and demonstrate the grain echo suppression capability of the algorithm in imaging applications.