Skywave Radar Research Articles

Application of Improved Sparrow Algorithm in Sky-Wave Radar Location

Application of Improved Sparrow Algorithm in Sky-Wave Radar Location

Societal Applications of HF Skywave Radar

After exploratory research in the 1950s, HF skywave ‘over-the-horizon’ radars (OTHR) were developed as operating systems in the 1960s for defence missions, notably the long-range detection of ballistic missiles, aircraft, and ships. The potential for a variety of non-defence applications soon became apparent, but the size, cost, siting requirements, and tasking priority hindered the implementation of these societal roles. A sister technology—HF surface wave radar (HFSWR)—evolved during the same period but, in this more compact form, the non-defence applications dominated, with hundreds of such radars presently deployed around the world, used primarily for ocean current mapping and wave measurements. In this paper, we examine the ocean monitoring capabilities of the latest generation of HF skywave radars, some shared with HFSWR, some unique to the skywave modality, and explore some new possibilities, along with selected technical details for their implementation. We apply state-of-the-art modelling and experimental data to illustrate the kinds of information that can be generated and exploited for civil, commercial, and scientific purposes. The examples treated confirm the relevance and value of this information to such diverse activities as shipping, fishing, offshore resource extraction, agriculture, communications, weather forecasting, and climate change studies.

A Cognitive Beamforming Method via Range-Doppler Map Features for Skywave Radar

For skywave over-the-horizon radar, beamforming techniques are often used to suppress airspace radio frequency interference because the high-frequency band is shared by many devices. To address the problems that the traditional beamforming method is not capable of recognizing the electromagnetic environment and that its performance is greatly affected by the accuracy of signal feature estimation, a cognitive beamforming method using range-Doppler (RD) map features for skywave radar is proposed. First, the RD map is weighted by a local attention model, and then, texture features are extracted as the inputs to a support vector machine. Finally, the support vector machine is used to predict the optimal diagonal loading factor. Simulation results show that the output signal-to-interference-plus-noise ratio is improved compared with previous methods. The proposed method is suitable for many kinds of common unsatisfactory scenarios, making it beneficial for engineering implementation.

Cognitive HF radar

Radars operating in the high-frequency (HF) band can exploit propagation modes other than line-of-sight and are hence widely employed to provide over-the-horizon surveillance and remote sensing. Most HF radars operating today rely on surface wave propagation; while opportunities for enhancing their performance by adding cognitive features exist, these have not been widely seized. In contrast, designers of HF skywave radars, which exploit ionospheric reflection to achieve ranges in excess of 4000 km, have long sought to counter the enormous challenges of the geophysical environment by implementing schemes to raise radar intelligence quotient (IQ) and autonomy. Measures that have been explored relate to resource allocation, operating procedures, signal processing, target classification and remote sensing. The perception–action cycle constitutes the structural element of these developments, accessing prior knowledge and input from auxiliary sensors, exactly as proposed by those who later coined the term cognitive radar. Here, the roles of cognition in HF skywave radars are reviewed, illustrating the needs and benefits with examples including detection in sea clutter, ionospheric channel compensation and multiple-input and multiple-output HF radar.

Editorial for Special Issue “Ocean Radar”

This Special Issue hosts papers related to ocean radars including the high-frequency (HF) surface wave and sky wave radars, X-, L-, K-band marine radars, airborne scatterometers, and altimeter. The topics covered by these papers include sea surface wind, wave and current measurements, new methodologies and quality control schemes for improving the estimation results, clutter and interference classification and detection, and optimal design as well as calibration of the sensors for better performance. Although different problems are tackled in each paper, their ultimate purposes are the same, i.e., to improve the capacity and accuracy of these radars in ocean monitoring.

A Novel Main-Lobe Cancellation Method Based on a Single Notch Space Filter and Optimized Correlation Analysis Strategy

The high-frequency hybrid sky-surface wave radar (HFSSWR) is a new kind of over-the-horizon radar system. Combining the advantages of both the sky wave radar and the surface wave radar, HFSSWR has drawn much attention in recent years. But the new system also brings new challenges. One of the most severe problems is that the heterogeneous environment makes a big challenge for the sea clutter suppression processing. Due to the nonstationary properties of the ionosphere, the first-order sea clutter statistics change significantly among range bins. So the new efficient sea clutter suppression method is required, and the clutter characteristics analyses are also in urgent need of research in order to guide the design of the algorithm in the background of HFSSWR. In this paper, utilizing the measured data set, we first analyse the range and spatial characteristics of the nonhomogeneous first-order sea clutter in HFSSWR. Then, an improved main-lobe cancellation (IMLC) method based on single notch space filter and correlation analysis is proposed to get training data which contains precise clutter information. A main-lobe clutter canceller based on the single notch space filter has been developed to block the target component, and an optimized correlation analysis (OCA) strategy is presented to choose the efficient training data. Finally, the method is examined by measured data and the results indicate that the method has a good performance for broadening first-order sea clutter suppression than the traditional method.

Coverage Area Analysis of Combined Sky-Wave and Surface-Wave Monostatic High Frequency Radar

High-frequency combined sky-wave and surface-wave monostatic radar (CSSM-HF RADAR) is a new type of radar system inspired by the skywave components of high-frequency surface-wave radar (HFSWR). The new type of radar uses the combined propagation paths of skywave and ground wave to detect targets, including four paths without considering ionospheric stratification. The related research of the CSSM-HF RADAR is relatively rare, and this paper carries out a detailed simulation analysis of its coverage area. Coverage area analysis is significant for subsequent work, such as target detection, frequency selection, and echo propagation path matching. In this paper, the signal-to-noise ratio (SNR) in the atmospheric background is derived at first, and then the parameters that change with propagation paths are analyzed. Finally, the coverage area of each propagation mode is calculated by setting the minimum detectable SNR. The simulation results show that the coverage areas of the four propagation paths at low frequency have overlapping regions. As the operating frequency increases, the coverage area of each propagation mode gradually separates, and some areas that cannot be covered may appear, however, the whole coverage area of the CSSM-HF RADAR increases.

基于改进灰狼算法的天波雷达定位模型

基于改进灰狼算法的天波雷达定位模型

Knowledge-Aided Ocean Clutter Suppression Method for Sky-Wave Over-the-Horizon Radar

In a sky-wave radar, the strong ocean clutter may cover up the echo signal of slow-speed targets. This letter proposed a knowledge-aided ocean clutter suppression method for the sky-wave radar. The proposed method uses the radar carrier frequency and the pulse repetition interval as prior knowledge to reconstruct the prior ocean clutter. This reconstructed clutter is combined with the ionosphere phase perturbation model. The resulting prior clutter is included in the optimal filter design. The simulation results show that the output signal-to-clutter plus noise ratio of this proposed method is 2.507 dB larger than the methods proposed by others.

Experimental analysis of a HF hybrid sky-surface wave radar

High-frequency (HF) radar systems exploit refractive and diffractive properties of HF waves to sense targets beyond the line of sight. HF skywave radars use the ionosphere medium to reflect the signals and thus illuminate targets of thousands of kilometers away, but they suffer from the close-distance blind zone and severe ionosphere decorrelation effect. HF surface wave radars exploit the diffraction of vertically polarized waves to detect targets within hundreds of kilometers offshore. But the diffracted surface wave is highly attenuated, and the radar has the vertical incidence ionospheric clutter problems. High-frequency hybrid sky-surface wave radar (HFSSWR) is a novel radar configuration containing a skywave transmitting path and a surface wave receiving path, which is a natural combination of HF skywave and HF surface wave radar systems [1]. In addition, multiple separate receiving sites can compose a multistatic network and operate with only one transmitter. The system configuration is flexible.

From the Editors of the Special Issue on HF Radar

This is the second of two issues of the IEEE Aerospace and Electronic Systems Magazine devoted to HF radar. The first issue, published in December 2017, contains seven papers dealing primarily with HF skywave radar; we refer readers to the editorial in that issue to acquaint themselves with the background to this publishing project, and to the papers therein to learn of some exciting developments in the field.

From the Editors of the Special Issue on HF Skywave Radar - continued from page 3

The articles in this special section address HF (high frequency) skywave radar technology and address a diverse range of issues that confront designers and users of HF radars.

From the Editors of the Special Issue on HF Skywave Radar

From the Editors of the Special Issue on HF Skywave Radar

The Big Data Processing of HF Sky-Wave Radar Sea Echo for Detection of Sea Moving Targets

A high-frequency (HF) sky-wave radar always monitoring large area of sea surface, for detecting sea surface moving objects, there must be big data waiting to be processed. A set of data processing methods were proposed, the successful implementation of HF sky-wave radar on the sea moving target detection. By setting the HF sky-wave radar parameters, after the initial data processing, the gotten HF sky-wave radar data were saved. Then a new HF sky-wave radar data processing method was provided, this method was the so-called three-step detection method (TSTM) which based on the constant false alarm rate (CFAR) technique. By using TSTM, setting the decision threshold G, with false alarms being ruled out, a moving target was detected out at last, its speed was calculated. The results also proved that TSTM could effectively reduce the sea clutter, and greatly lessen the echo-broadening and double-image caused by ionosphere contamination.

Approach for transient interference detection based on straight line extraction for high‐frequency sky‐wave radar

Transient interference cancellation is necessary for high-frequency sky-wave radar and usually requires accurate interference detection and localisation which is complicated due to the non-uniform noise level caused by sea-clutter mitigation in Doppler domain. A novel approach is proposed by converting the detection of interference into a problem of straight line extraction in the constructed fast- and slow-time images. The line edges are detected by an edge detector, such as Canny method, followed by Hough transform. Then, each edge is classified as a rising, falling or false-alarm edge based on multi-threshold segmentation of image sub-blocks. Experimental results demonstrate the effectiveness of the proposed approach.

Ionospheric decontamination based on sparse reconstruction for skywave radar

Ionospheric phase decontamination is the key factor to improve the target detection capability of skywave radar. In this paper, a new ionospheric phase decontamination algorithm is proposed based on sparse reconstruction. We transform the problem of estimating ionospheric contamination phase into a sparse optimization problem, then solve it rapidly by the iterative method to get the modulation frequency caused by ionospheric phase contamination. Compared with the existing algorithms, the proposed algorithm in this paper has the following advantages: 1. higher accuracy is obtained under the situation of both fast phase fluctuation and slow phase fluctuation; 2. the proposed algorithm is more robust to noise; 3. real-data processing results of the proposed algorithm are better.

Post-Doppler Adaptive Digital Beamforming of Skywave Radar

Post-Doppler Adaptive Digital Beamforming of Skywave Radar

An OPMA for Robust Mutual Coupling Coefficients Estimation of URA with Single Snapshot in MIMO HF Sky-Wave Radar

Due to the fluctuation of the signal-to-noise ratio (SNR) and the single snapshot case in the MIMO HF sky-wave radar system, the accuracy of the online estimation of the mutual coupling coefficients matrix of the uniform rectangle array (URA) might be degraded by the classical approach, especially in the case of low SNR. In this paper, an Online Particle Mean-Shift Approach (OPMA) is proposed, which is to get a relatively more effective estimation of the mutual coupling coefficients matrix with the low SNR. Firstly, the spatial smoothing technique combined with the MUSIC algorithm of URA is introduced for the DOA estimation of the multiple targets in the case of single snapshot which are taken as coherent sources. Then, based on the idea of the particle filter, the online particles with a moderate computational complexity are used to generate some different estimation results. Finally, the mean-shift algorithm is applied to get a more robust estimate of the equivalent mutual coupling coefficients matrix. The simulation results demonstrate the validity of the proposed approach in terms of the success probability, the statistics of bias, and the variance. The proposed approach is more robust and more accurate than the other two approaches.

Propagation effects on high frequency skywave multiple‐input–multiple‐output radar

Multiple-input–multiple-output (MIMO) technology has been suggested as an effective tool in overcoming some of the issues that are typically relate to conventional over the horizon radars. Notwithstanding, effects, such as fading and multipath propagations are ever present and cannot be avoided even when using a MIMO configuration. For this reason, a study on the impact of such effects on high frequency (HF) skywave MIMO radars is fundamental for an effective design of such systems. This study aims to study the effects of ionospheric propagation on the performance of the HF MIMO skywave radar. In particular, the relationship between the transmitted signal parameters and the ionospheric variations because of perturbations is highlighted in a suitable signal model. The performance analysis is performed in terms of estimated direction of arrival and loss of virtual array elements.

A Skywave OTHR Adaptive Frequency Selection Method Based on Preliminary Criterion and Weighted Criterion

A skywave radar adaptive frequency selection method based on the preliminary criterion and the weighted criterion is presented. In this method, according to the various operational tasks, the frequency selection criterion is divided into the preliminary criterion and the weighted criterion based on the characteristic of the targets. The adaptive frequency selection of the skywave radar is achieved by the weighted computed of the frequency selection criterion. The feasibility and availability is demonstrated by an example.