Over-the-horizon Radar Research Articles

JIE for a class of MD systems

In multi-detection (MD) systems including over-the-horizon radar (OTHR) systems, the forward-based receivers systems and passive coherent location systems, resolvable multiple detections of one target due to the multi-path propagation will be received, in which both identification (including measurement association and propagation mode/transmitting origin identification) and estimation (including path-conditional state estimation and multi-path track fusion) are deeply coupled and affect each other. Up to present, all corresponding methods fall into the scope of sequential identification orientated or estimation orientated processing, and hence the solutions are not satisfactory. Here the joint identification and estimation scheme for the MD systems (MD-JIE) is developed based on the generalized Bayes risk considering both identification and estimation performance. The likelihood-ratio function and the conditional probability density function as the identification cost and estimation cost are recursively calculated, respectively. Taking the data-association constraints into consideration, the proposed MD-JIE scheme is implemented via online constrained optimization technology. Compared to the identification-then-estimation (ITE) method and the estimation-then-identification (ETI) method, the proposed MD-JIE method prevails in the joint performance measure with the higher correct identification rate than the ETI method and the smaller root MSE than the ITE method. Besides, the robustness of the proposed method is verified.

Sea Clutter Suppression Method for Over-the-horizon Radar with Short Coherent Integration Time Based on Compressed Sensing

To deal with the drawbacks of low reconstruction accuracy and poor suppression performance of clutter with short Coherent Integration Time (CIT) for traditional time domain cancellation method, a method of sea clutter reconstruction and suppression based on Compressed Sensing (CS) is proposed. Firstly, echoes model of Over-The-Horizon Radar (OTHR) with short CIT is established, and the rationality using CS to reconstruct sea clutter is analyzed. Secondly, the proposed method is elaborated in detail from sparse representation of echoes model based on redundant sinusoidal?dictionary, representation of sensing matrix based on dimensionality reduction dictionary and sea clutter reconstruction and suppression based on the modified Orthogonal Matching Pursuit (OMP) algorithm respectively. Finally, the computer simulation analysis and measured data verification are accomplished. The results indicate that the clutter suppression performance and engineering application value of the proposed method are better than the traditional time domain cancellation method and subspace methods in the condition of short CIT.

Stacked Autoencoders for Outlier Detection in Over-the-Horizon Radar Signals.

Detection of outliers in radar signals is a considerable challenge in maritime surveillance applications. High-Frequency Surface-Wave (HFSW) radars have attracted significant interest as potential tools for long-range target identification and outlier detection at over-the-horizon (OTH) distances. However, a number of disadvantages, such as their low spatial resolution and presence of clutter, have a negative impact on their accuracy. In this paper, we explore the applicability of deep learning techniques for detecting deviations from the norm in behavioral patterns of vessels (outliers) as they are tracked from an OTH radar. The proposed methodology exploits the nonlinear mapping capabilities of deep stacked autoencoders in combination with density-based clustering. A comparative experimental evaluation of the approach shows promising results in terms of the proposed methodology's performance.

A New Method for Multipath Clustering for Over-the-Horizon Radar

Over-the-Horizon Radar (OTHR) exploits the refraction of high frequency radiation through the ionosphere layers to detect targets beyond the line-of-sight horizon. Multipath propagation between the radar and the detected targets may results in multiple spatially separated tracks for a single target to be observed at the receiver site. Consequently there is a heavy traffic, especially in case of multiple targets, to be associated and combined if there are tracks represent the same target. In this study, a new method for multipath clustering for OTHR is proposed. The proposed method describes the similarities between all tracks as fuzzy degrees of membership. This method can operate in real-time and can perform clustering and fusion of OTHR tracks with tracks from other sources such as targets reporting global positioning systems and microwave radars. The proposed method has the advantages of less computations and high efficiency compared to conventional fuzzy logic clustering techniques. It has also the advantage of treating all the tracks data at once rather than pairwise. The efficiency of the proposed method is demonstrated using simulated examples.

Transient interference suppression for high‐frequency skywave over‐the‐horizon radar

Skywave over-the-horizon radar (OTHR) plays an important role in the out-of-sight surveillance. However, the operational performance will severely degrade due to transient interferences. Previous works concentrate on time-domain methods to achieve transient interference suppression. However, time-domain methods are usually time-consuming and suffer performance loss when several discontinuous transient interference segments occupy parts of coherent processing interval. In fact, most transient interferences are spatially structured and can be cancelled at adaptive beamforming stage. In this study, the adaptive beamforming is adopted and a space-time cascade processing procedure is proposed for transient interference suppression. In the procedure, the sidelobe transient interferences are cancelled by adaptive beamforming and the mainlobe transient interferences are suppressed by a modified time-domain method. The proposed procedure is in accordance with the regular processing procedure of skywave OTHR and can provide reliable performance with small extra computational costs. The performance of the proposed procedure is evaluated using experimental data recorded by a trial skywave OTHR and the results verify the feasibility and effectiveness of the proposed procedure.

Computationally Efficient Transient Interference Excision Method for Skywave Over-the-Horizon Radar

The skywave over-the-horizon radar (OTHR) has attracted considerable attention for its ability of out-of-sight surveillance. However, in practice, its operational performance is severely degraded by transient interferences. Some previous works focus on time-domain methods to achieve transient interference suppression and cannot get rid of the corruption segment blanking and data interpolation. In fact, the data interpolation method is usually time-consuming and may suffer performance loss. To avoid data interpolation, some interpolation-free methods are proposed and show superior performance. However, the significant computational costs impede the application in reality. In this letter, a new method for transient interference suppression is proposed. After interference localization, a signal subspace, representing the clutter and target, is constructed by the interference-free data. Then, transient interferences are excised by solving a bicriterion optimization problem that minimizes the quadratic fitting error and the energy orthogonal to the signal subspace simultaneously. The proposed method can excise transient interferences with clutter and potential target echoes preserved at the same time; thus, data interpolation is no longer needed. The proposed method is evaluated by experimental data collected from a trial skywave OTHR, and the results verify its effectiveness.

Parameter estimation of maneuvering targets in OTHR based on sparse time-frequency representation

This paper proposes a new method for estimating the parameter of maneuvering targets based on sparse time-frequency transform in over-the-horizon radar (OTHR). In this method, the sparse time-frequency distribution of the radar echo is obtained by solving a sparse optimization problem based on the short-time Fourier transform. Then Hough transform is employed to estimate the parameter of the targets. The proposed algorithm has the following advantages: Compared with the Wigner-Hough transform method, the computational complexity of the sparse optimization is low due to the application of fast Fourier transform (FFT). And the computational cost of Hough transform is also greatly reduced because of the sparsity of the time-frequency distribution. Compared with the high order ambiguity function (HAF) method, the proposed method improves in terms of precision and robustness to noise. Simulation results show that compared with the HAF method, the required SNR and relative mean square error are 8 dB lower and 50 dB lower respectively in the proposed method. While processing the field experiment data, the execution time of Hough transform in the proposed method is only 4% of the Wigner-Hough transform method.

Target location and height estimation via multipath signal and 2D array for sky-wave over-the-horizon radar

In sky-wave over-the-horizon radar (OTHR), it is quite difficult to handle the issues of target location (ground range) and height (altitude) estimation due to their joint effect on group range. This work addresses the joint estimation of target location and height by the means of multipath propagation of OTHR signals and structure of a two-dimensional (2D) array. Usually, the multipath signal results from ionosphere propagation in OTHR and can be produced in multi-input–multi-output (MIMO) radar by transmitting signals of various carrier frequencies. A 2D array provides the potential of elevation resolution, which is related to ground and slant ranges. By the multi-quasi-parabolic (MQP) ionospheric model, we formulate the multipath propagation and signal model for the OTHR with a target at location r and height h. Moreover, the joint maximum-likelihood estimates (MLEs) of r and h are derived, and the joint Fisher information matrix (FIM) is calculated. With the so-obtained FIM, the estimability is analyzed; that is: r and h are estimable if and only if either a multipath signal or 2D array is available. The joint Cramer-Rao bound (CRB) is computed and discussed for accuracy improvement. Additionally, the estimability is also extended to the joint estimation of target location, height, and velocity.

Modeling the interference environment in the HF band

AbstractThe performance of systems using high frequency (HF) radio waves, such as over‐the‐horizon radars (OTHR), can be strongly affected by external interferers at great distances (thousands of kilometers) from the systems receiver. However, the propagation of interference has complex behavior and is known to vary with location, time, season, sunspot number, and radio frequency. Understanding how the level of interference varies with all of these factors is important for the design of new systems such as next generation OTHR. By combining databases of known transmitters, ray‐tracing propagation, and a model ionosphere, a model of the behavior of interference at HF has been developed.

Radio Frequency Interference Cancelation for Skywave Over-the-Horizon Radar

In the user-congested high-frequency band, skywave over-the-horizon radar (OTHR) is easily interfered by radio frequency interference (RFI). Among the existing methods, transient and nontransient RFIs are suppressed by time-domain methods and beamforming methods, respectively. However, the existing beamforming methods cannot work in transient cases, whereas the time-domain methods are usually time-consuming and suffer performance loss in mass interference cases. Therefore, a unified method for two kinds of RFI cancelation is preferred. In this letter, based on the frequency characteristics of the RFI and the regular processing procedure of the skywave OTHR, an adaptive RFI cancelation scheme is proposed. In this scheme, the RFI is localized in the frequency domain, after which snapshots are chosen to complete the frequency-domain adaptive beamforming. The proposed scheme makes it possible to completely cancel both kinds of RFI in the beamforming stage, which is timesaving and proper for practical application. The performance of the proposed scheme is evaluated by experimental data.

MIMO-OTHR WAVEFORM OPTIMIZATION BASED ON THE MUTUAL INFORMATION THEORY

In traditional over-the-horizon radar (OTHR), multipath propagation due to the multi- layer ionospheric structure always deteriorates the detection performance. The properties of multiple- input multiple-output (MIMO) radar technique, which transmits wide beams with low gain at the transmitter and achieves receiver beam-forming to obtain narrow beams with high gain, make it an ideal choice for OTHR to detect target through multi-layer ionosphere and suppress strong clutter. This paper investigates the assumption of a two-layer ionospheric model and proposes a two-step Max- Min algorithm based on the mutual information theory to optimize MIMO-OTHR waveform so as to suppress clutter, interference and noise. The first step is to maximize the mutual information between the echo and target response from the same direction of arrival (DOA) in order to reduce the impact of noise. The second step is to minimize the mutual information between the echoes from different DOAs, in order to suppress the clutter and interference by reducing the correlation of the echoes from the different DOAs. Numerical experiments validate that this algorithm can improve range resolution and detection probability significantly. Experiment results also demonstrate that the previously harmful multipath propagation can be utilized to enhance the detection performance in MIMO-OTHR.

Gaussian mixture probability hypothesis density filter for multipath multitarget tracking in over-the-horizon radar

Conventional multitarget tracking systems presume that each target can produce at most one measurement per scan. Due to the multiple ionospheric propagation paths in over-the-horizon radar (OTHR), this assumption is not valid. To solve this problem, this paper proposes a novel tracking algorithm based on the theory of finite set statistics (FISST) called the multipath probability hypothesis density (MP-PHD) filter in cluttered environments. First, the FISST is used to derive the update equation, and then Gaussian mixture (GM) is introduced to derive the closed-form solution of the MP-PHD filter. Moreover, the extended Kalman filter (EKF) is presented to deal with the nonlinear problem of the measurement model in OTHR. Eventually, the simulation results are provided to demonstrate the effectiveness of the proposed filter.

Method to suppress transient interference in skywave OTHR

In skywave over-the-horizon radar (OTHR), transient interference is always suppressed with steps of interference localisation, corruption segment blanking and data restoration. The gapped data amplitude and phase estimation (GAPES) method has been proved to achieve good restoration performance. However, the large computational cost limits its application. A computationally efficient method for transient interference suppression is proposed. Quadratic smoothing is used to suppress transient interference instead of blanking the contaminated data. After that, the GAPES method only needs to restore the smoothed target echoes. Since quadratic smoothing can preserve most clutter echoes, the GAPES method will converge much faster. Experimental results demonstrated the effectiveness of the proposed method.

Transient interference excision and signal recovery in OTHR using robust principal component analysis

The performance of high-frequency wave over-the-horizon radar (OTHR) is affected by transient interference. Transient interference suppression results in the integrity of the target signal. Without suppressing on clutter before interference excision, a robust principal component analysis is applied to separate clutter and the target signal, and the target signal is recovered simultaneously. Experimental results show the effectiveness of the proposed method.

Trajectory optimisation method by using independent component analysis for MIMO‐OTHR target tracking

Traditional sky-wave over-the-horizon radar (OTHR) target tracking algorithms, such as multipath probabilistic data association, can achieve good performance if the multipath environment clutter is not strong enough. The computation complexity and tracking performance of these algorithms can be further improved by multiple-input multiple-output (MIMO) radar technology owing to its capability to utilise transmitting and receiving diversities. However, multipath propagation is still considered to degrade the performance because of the strong ionosphere and sea clutter. To deal with the interference of strong clutter in a multipath environment, a tracking trajectory optimisation method is proposed by applying the fast and robust fixed-point independent component analysis algorithm which uses the projection pursuit approach to separate clutter and a true target moving trajectory from the received signals. Numerical simulations demonstrate the feasibility of the method, and it also shows that the multipath measurements can be utilised for MIMO-OTHR target tracking.

Analyzing potential over-the-horizon radar site locations

Over-the-horizon radar (OTHR) systems, or skywave propagation systems, use the high frequency (HF) band (3 to 30 MHz) to “bounce” or “refract” a signal off the ionosphere to detect tracks of interest (TOIs) between 500 and 2000 nautical miles from the transmitter/receiver pair. This range is “an order of magnitude greater than is possible with conventional line-of-sight radars” [1]. Since their initial employment, OTHR systems have significantly improved in abilities to detect and track TOIs such as aircraft, ballistic and cruise missiles, and ships [2].

A Multiple-Detection Probability Hypothesis Density Filter

Most conventional target tracking algorithms assume that one target can generate at most one detection per scan. However, in many practical target tracking applications, one target may generate multiple detections in one scan, because of multipath propagation, or high sensor resolution or some other reason. If the multiple detections from the same target can be effectively utilized, the performance of the multitarget tracking system can be improved. However, the challenge is that the uncertainty in the number of targets and the measurement set-to-target association will increase the complexity of tracking algorithms. To solve this problem, the random finite set (RFS) modeling and the random finite set statistics (FISST) are used in this paper. Without any extra approximation beyond those made in the standard probability hypothesis density (PHD) filter, a general multi-detection PHD (MD-PHD) update formulation is derived. It is also established in this paper that, with certain reasonable assumptions, the proposed MD-PHD recursion can function as a generalized extended target PHD or multisensor PHD filter. Furthermore, a Gaussian Mixture (GM) implementation of the proposed MD-PHD formulation, called the MD-GM-PHD filter, is presented. The proposed MD-GM-PHD filter is demonstrated on a simulated over-the-horizon radar (OTHR) scenario.

Correction’s method of the electron density model in ionosphere by ray tracing techniques

When applying the ray tracing in ionospheric propagation, the electron density modelling is the main input of the algorithm, since phase refractive index strongly depends on it. Also the magnetic field and frequency collision modelling have their importance, the former as responsible for the azimuth angle deviation of the vertical plane containing the radio wave, the latter for the evaluation of the absorption of the wave. Anyway, the electron density distribution is strongly dominant when one wants to evaluate the group delay time characterizing the ionospheric propagation. From the group delay time, azimuth and elevation angles it is possible to determine the point of arrival of the radio wave when it reaches the Earth surface. Moreover, the procedure to establish the target (T) position is one of the essential steps in the Over The Horizon Radar (OTHR) techniques which require the correct knowledge of the electron density distribution. The group delay time generally gives rough information of the ground range, which depends on the exact path of the radio wave in the ionosphere. This paper focuses on the lead role that is played by the variation of the electron density grid into the ray tracing algorithm, which is correlated to the change of the electron content along the ionospheric ray path, for obtaining a ray tracing as much reliable as possible. In many cases of practical interest, the group delay time depends on the geometric length and the electron content of the ray path. The issue is faced theoretically, and a simple analytical relation, between the variation of the electron content along the path and the difference in time between the group delays, calculated and measured, both in the ionosphere and in the vacuum, is obtained and discussed. An example of how an oblique radio link can be improved by varying the electron density grid is also shown and discussed.

Ionosphere phase decontamination method based on subspace in sky‐wave OTHR

In general, ionosphere phase contamination can expand the Bragg peak of sea clutter and the echo signal from a target in sky-wave over-the-horizon radar (OTHR). By exploiting the subspace algorithm, an effective approach of ionosphere phase decontamination is proposed to solve the above-mentioned problems. In this new scheme, the stronger one of two spreading Bragg peaks is extracted by an adaptive sliding-window bandpass filter, and the instantaneous phase of the spreading Bragg peak is obtained by the subspace algorithm. Both the theoretical analysis and the experimental results of the real OTHR data have confirmed the feasibility of this new method.

Wideband signal design for over-the-horizon radar in cochannel interference

Ship detection in heavy sea clutter is a big challenge for over-the-horizon (OTH) radar. Wideband signal is helpful for improving range resolution and the signal-to-clutter ratio. In this paper, to support OTH radar employing wideband in cochannel interference, we propose environmental sensing-based waveform (ESBW) strategy, by considering transmit waveform design as an active approach and cognitive loop for the time-varying environment. In ESBW strategy, OTH radar monitors the environment in real time, estimates interference characteristics, designs transmit waveform adaptively, and employs traditional signal processing structure to detect targets in the presence of interference. ESBW optimization problem employs the criteria of maximizing the output signal-to-interference-plus-noise ratio (SINR) of matched filter and similarity constraint for reasonable range resolution and sidelobe levels. The analytic solution to this constrained problem is developed, so that ESBW design algorithm’s efficiency is guaranteed, with adjustable SINR and autocorrelation function. A simulated scenario with strong interference and colored noise has been introduced. Simulation results demonstrate that OTH radar with ESBW strategy detects the target successfully in the background of cochannel interference.