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Pareto distribution has been introduced into the radar community recently as a suitable model for X-band high resolution maritime sea clutter returns. This intensity clutter model is a simple two parameter power law distribution. It is thus important to consider the development of constant false alarm rate detection processes for targets embedded within such clutter. It is shown that a simple functional transform can produce such detection schemes, whose false alarm probability and threshold are related through simple analytical expressions. These relationships are related intrinsically to Gaussian detection counterparts. Three detectors will be introduced and their performance analysed in both homogeneous and heterogeneous clutter environments. The effect of interfering targets in the training cells will also be examined.

This study examines ground and sea clutter from three different FM-based passive bistatic radars (PBRs). Measurement data has been obtained for low-grazing angles. The PBRs used to collect the displayed data, with all their relevant parameters, are defined and clutter analysis procedures are described. This work, based on measured data, yields valuable insight into the nature of VHF bistatic clutter.

The Earth's surface radar reflection is one of the most important signals received by spaceborne radar systems. It is used in several scientific applications, including geolocation, terrain classification, and path-integrated attenuation estimation. A simulator based on the ray-tracing approach has been developed to reproduce the clutter reflectivity and the Doppler velocity signal for a conically scanning spaceborne Doppler radar system. The simulator exploits topographic information through a raster digital elevation model, land types from a regional classification database, and a normalized radar surface cross-section look-up table. The simulator is applied to the WInd VElocity Radar Nephoscop (WIVERN) mission, which proposes a conically scanning W-band Doppler radar to study in-cloud winds. Using an orbital model, detailed simulations for conical scans over the Piedmont region of Italy, which offers a variety of landscape conditions, are presented. The results highlight the strong departure of the reflectivity and Doppler velocity profiles in the presence of marked orography and the significant gradient in the surface radar backscattering properties. The simulations demonstrate the limitations and advantages of using the surface Doppler velocity over land as an antenna-pointing characterization technique. They represent the full strength range of the surface radar clutter over land surfaces for the WIVERN radar. The surface clutter tool applies to other spaceborne radar missions, such as the nadir-pointing EarthCARE and CloudSat Cloud Profiling Radar (CPR), or the cross-track scanning Global Precipitation Measurement (GPM) precipitation radars.

The Multi-Radar-Multi-Sensor (MRMS) system was transitioned into operations at the National Centers for Environmental Prediction in the fall of 2014. It provides high-quality and high-resolution severe weather and precipitation products for meteorology, hydrology, and aviation applications. Among processing modules, the radar data quality control (QC) plays a critical role in effectively identifying and removing various nonhydrometeor radar echoes for accurate quantitative precipitation estimation (QPE). Since its initial implementation in 2014, the radar QC has undergone continuous refinements and enhancements to ensure its robust performance across seasons and all regions in the continental United States and southern Canada. These updates include 1) improved melting-layer delineation, 2) clearance of wind farm contamination, 3) mitigation of corrupt data impacts due to hardware issues, 4) mitigation of sun spikes, and 5) mitigation of residual ground/lake/sea clutter due to sidelobe effects and anomalous propagation. This paper provides an overview of the MRMS radar data QC enhancements since 2014.

In order to solve the problem of maritime targets tracking in heavy-tailed sea clutter with unknown and time-varying clutter density, a multi-scan clutter sparsity estimator based amplitude-aided probability hypothesis density (MCSE-APHD) method is proposed in this paper. Firstly, the proposed method eliminates the target-originated measurements from multi-scan cumulative measurement set and estimates the spatial distribution density of clutter online. And the estimated clutter density parameter is fed to the tracker. Secondly, the amplitude-aided likelihood function as well as the estimated clutter parameter is established to update the Gaussian mixture posterior intensity of the state using the probability hypothesis density algorithm. The simulation results verify the effectiveness of the proposed algorithm.

The spaceborne-airborne bistatic radar (SABR) system employs a spaceborne transmitter and an airborne receiver, offering significant advantages, such as wide coverage, outstanding anti-stealth capabilities, and notable resistance to jamming. However, SABR operates in a downward-looking configuration, and due to the separation of the transmitter and receiver, non-side-looking array reception, and the effects of Earth’s rotation, clutter exhibits both spatial-temporal coupling and distance dependence. These factors cause substantial expansion in spatial and temporal frequency domains, leading to severe degradation in radar detection performance for moving targets. This paper establishes an SABR clutter signal model that applies to arbitrary geometric configurations to respond to these challenges. The paper uses this model to analyze the non-side-looking clutter characteristics in a geostationary spaceborne-airborne bistatic radar configuration. Furthermore, the paper investigates the impact of various observation areas and geometric configurations on detection performance, using SCNR loss as the performance index. Finally, this paper gives suggestions on the transceiver’s geometric configuration and the observation area selection.

This letter proposes a data‐driven method to simulate random sea clutter amplitude sequence with distribution and correlation characteristics directly inherited from the measured clutter. First, a generation model is developed to simulate clutter amplitude sequence with desired distribution. By multiplying the measured amplitudes with random disturbance coefficients, the model introduces sample diversity between the simulated and measured sequences. Meanwhile, to quantitatively control the difference of the distribution tails between the simulated and measured sequences (i.e. to ensure their distributions are similar), the threshold error metric is introduced to set the disturbance variance. Second, a scheme combining the generation model with the correlation transfer technique is presented, which allows to simulate clutter amplitude sequence with both desired distribution and correlation for engineering purpose. Experiments based on different measured clutter sets indicate the proposed method works very well.

The target and sea clutter Doppler domains frequently overlap due to the frequent passage of slow ship targets through the sea clutter zone. In this letter, a novel sea clutter suppression method is suggested as a solution to this issue, whose key is a novel singular value zeroing criterion guided by the search results of two‐dimensional spectral peaks. Verified by simulations, the method proposed can improve signal‐to‐clutter ratio (SCR) from −8 to 41 dB in the frequency domain and be more effective than the conventional SVD‐FRFT (a method for joint application of singular value decomposition and fractional Fourier transformer) and improved SVD‐FRFT. The target and sea clutter Doppler domains frequently overlap due to the frequent passage of slow ship targets through the sea clutter zone. In this letter, a novel sea clutter suppression method is suggested as a solution to this issue, whose key is a novel singular value zeroing criterion guided by the search results of two‐dimensional spectral peaks. Verified by simulations, the method proposed can improve signal‐to‐clutter ratio (SCR) from −8 dB to 41 dB in the frequency domain and be more effective than the conventional SVD‐FRFTï¼a method for joint application of singular value decomposition and fractional Fourier transformer) method in[7] and improved SVD‐FRFT method in[8] .

Sea clutter introduces a significant amount of non-target reflections in the echo signals received by radar, complicating target detection and identification. To address the challenge of existing filter parameters being unable to adapt in real-time to the characteristics of sea clutter, this paper integrates ocean numerical models into the sea clutter spectrum estimation. By adjusting filter parameters based on the spectral characteristics of sea clutter, the accurate suppression of sea clutter is achieved. In this paper, the Weather Research and Forecasting (WRF) model is employed to simulate the ocean dynamic parameters within the radar detection area. Hydrological data are utilized to calibrate the parameterization scheme of the WRF model. Based on the simulated ocean dynamic parameters, empirical formulas are used to calculate the sea clutter spectrum. The filter coefficients are updated in real-time using the sea clutter spectral parameters, enabling precise suppression of sea clutter. The suppression algorithm is validated using X-band radar-measured sea clutter data, demonstrating an improvement factor of 17.22 after sea clutter suppression.

This article presents the statistical analysis of bistatic radar rural ground clutter for different terrain types under low grazing angles. Compared to most state-of-the-art analysis, we present country-specific clutter analysis for subgroups of rural environments rather than for the rural environment as a whole. Therefore, the rural environment analysis is divided into four dominant subgroup terrain types, namely fields with low vegetation, fields with high vegetation, plantations of small trees and forest environments representing a typical rural German environment. We will present the results for both the summer and the winter vegetation. Therefore, bistatic measurement campaigns have been carried out during the summer 2019 and the winter of 2019/20 in the aforementioned four different rural terrain types. The measurements were performed in the radar relevant X-band at a center frequency of 8.85 GHz and over a bandwidth of 100 MHz according to available transmit permission. The distinction of the rural terrain into different subgroups enables a more precise and accurate clutter analysis and modeling of the statistical properties as will be shown in the presented results. The statistical properties are derived from the calculated clutter amplitudes probability density functions and corresponding cumulative distribution functions for each of the four terrain types and the corresponding season. The data basis for the clutter analysis are the processed range-Doppler maps from the bistatic radar measurements. According to the authors’ current knowledge, a similar investigation based on real bistatic radar measurement data with the division into terrain subgroups has not yet been carried out and published for a German rural environment.