Over-the-horizon Research Articles

A DPD Algorithm of Maximum Likelihood Based on DOAs and Doppler

Direct position determination (DPD) is a single step method that estimates the position of target by received signals. Localization in 3D scene is a complicated problem, because the signal propagation channel is complex, and it has many kinds of interference and noise. This paper establishes the Over-the-horizon (OTH) shortwave signals and line-of-sight propagation of ultra short wave model, and proposes a joint localization algorithm. We compare the Cramér-Rao Bound(CRB) and the root mean square error (RMSE) between the proposed algorithm and DPD used single information like DOA and Doppler. The simulation results verify the superiority of the proposed algorithm, and prove it has higher accuracy.

CLIMF2: A climatological model of the ionospheric F2 layer. Part 2: Validation and comparison with IRI

Accurate models of the ionospheric F2 layer are required for many applications dependent on the propagation of radio waves through the ionosphere, such as over-the-horizon (OTH) radar, high frequency (HF) communications, global navigation satellite systems (GNSS), and low-frequency radio astronomy. CLIMF2 is a new model of the ionospheric F2 layer parameters, foF2 and hmF2, which provides the variance in these parameters as well as the median, and can be used in conjunction with IRI. Currently available climatological models are only able to provide the monthly median and so CLIMF2 represents a significant enhancement to climatological modelling of the ionosphere. An assessment of the performance of the CLIMF2 monthly median results against vertical incidence sounder (VIS) observations and a comparison against IRI are presented in this paper. The models of foF2 and hmF2 in CLIMF2 and IRI perform relatively similarly, with improvement provided by CLIMF2 especially at times around sunrise. An assessment of the CLIMF2 tenth and ninetieth percentile foF2 and hmF2 values against VIS data is also presented.

CLIMF2: A climatological model of the ionospheric F2 layer. Part 1: Model methodology

The ionospheric F2 layer is of key importance to systems dependent on the propagation of radio waves through the ionosphere, including over-the-horizon (OTH) radar, high frequency (HF) communications, global navigation satellite systems (GNSS), and low-frequency radio astronomy. The currently accepted F2 layer model, the International Reference Ionosphere (IRI), does not provide the variance in the parameters used to describe the layer and furthermore, was developed from a limited dataset. The newly developed model, CLIMF2, can be used in conjunction with IRI to overcome these limitations, and thereby improve applications such as the climatological modelling of OTH radar performance. CLIMF2 is an empirical climatological model of the F2 layer parameters derived from a global network of vertical incidence sounder (VIS) observations, consisting of 267 sites with data from the 1950s to 2021. CLIMF2 has the added functionality of providing the variance in the foF2 and hmF2 parameters.

Multi-channel track-before-detect approach for airborne target with OTH radar

It is a common requirement for over-the-horizon (OTH) radar to detect the sea and airborne targets in the same direction simultaneously. The long coherent integration time (CIT) is needed to detect the sea target and the weak moving target such as aircraft. However, the range walk effect (RWE) will occur within the long integration time, leading to a serious degradation of the airborne target detection and tracking. To settle this problem, a new approach based on the multi-channel track-before-detect (MC-TBD) is proposed in this paper. More specifically, to improve the detection performance of the airborne target with unknown speed, multiple processing channels corresponding to different speed ranges are set under the MC-TBD framework. The received data are processed in each channel in parallel. In each channel, the constraints of the speed range are utilized to determine the number of pulses in the CIT of the airborne target. Then, coherent and noncoherent integration processing are performed sequentially based on the moving target detection (MTD) and track-before-detect (TBD). Finally, the detection results and trajectories of all channels are fused to achieve the final detection and tracking of the airborne target. Simulation results show the superiority of the proposed MC-TBD approach over the existing methods in terms of the performance of detection and tracking for airborne target with OTH radar under the background of simultaneous detection of airborne and sea targets in the same direction.

The Effects of Rainfall on Over-the-Horizon Propagation in the Evaporation Duct over the South China Sea

The evaporation duct (ED) is generated by the evaporation of seawater and can be an influential factor of electromagnetic (EM)-wave propagation. Rainfall also affects atmospheric factors and EM-wave propagation. However, the distribution of the ED and path loss (PL) during rainfall has rarely been reported. This paper analyzes the distribution of the atmospheric factors and ED in the South China Sea (SCS). The results show that the evaporation duct height (EDH) in the area of rainfall is generally lower. The effect of the ED on the over-the-horizon (OTH) propagation reaches 0.69 dB km−1 on average, which is 4.3 times stronger than the maximum rain attenuation (0.16 dB km−1) when the rainfall is less than 5 mm h−1. In the SCS, a 53 km long OTH link was established between Donghai Island and Jizhao Bay to observe the PL. The measurement results show that the nearly saturated relative humidity (RH) leads to a high PL. The results also show that the change in the direction of the sea–land breeze causes a 42.4 dB decrease of PL by transferring the moist patches. Rainfall has an attenuation effect on OTH propagation in ED, mainly owing to the high RH.

Combination of Land-Based and Satellite-Based OTH Geolocations Using Differentiable Exact Penalty Method

In civil or military applications, a transmitter on Earth may utilize different means of communications. A typical example is the naval craft, which often radiates very high frequency signals received by a satellite system and high frequency signals received by land-based observers. This article concentrates on the combination of land-based and satellite-based over-the-horizon (OTH) geolocations. A quadratic constrained weighted least-squares optimization model for the combined geolocation is established and a differentiable exact penalty solution is developed to locate the OTH transmitter in an iterative manner, which is shown to have robust convergence performance. Theoretical analysis is presented, which involves the Cramér–Rao bound for combined geolocation under the constraint of ellipsoidal Earth model and the closed-form expression of mean square error for the proposed method. Numerical examples are provided to validate our theoretical analysis and illustrate that the proposed method outperforms other geolocation methods in a wide range of scenarios.

A Single-Step Method for Over-the-Horizon Geolocation Using Importance Sampling

This paper investigates the geolocation for an over-the-horizon (OTH) transmitter observed by widely separated arrays. We propose a maximum likelihood (ML) based direct position determination (DPD) method to directly locate the transmitter in a single step by exploiting the position information embedded in azimuth angles. The Monte Carlo importance sampling (IS) technique is employed to find an approximate global solution to this DPD problem, where the importance function analogous to Gaussian distribution is derived. This enables the transmitter to be precisely located with low complexity in a noniterative manner. Additionally, we derive the Cramér–Rao bound (CRB) expression for the investigated problem. The simulation results corroborate the superior localization performance of the proposed method with respect to the conventional two-step approaches and the iterative DPD method.

IoT OTH Maritime Surveillance Service over Satellite Network in Equatorial Environment: Analysis, Design and Deployment

This paper explores the challenges and constraints when over the horizon (OTH) maritime surveillance service utilizes an Internet of Things (IoT) as its backbone. The service is based on High Frequency Surface Wave Radars (HFSWRs) and relies on a satellite communication network as its communication infrastructure in harsh environments. The complete IoT OTH maritime surveillance network is currently deployed in the Gulf of Guinea, which due to its tropical climate represents an unfavorable environment for sensors and communications. In this paper, we have examined the service performance under various meteorological conditions specific to the Gulf of Guinea. To the best of our knowledge, this is the first analysis of IoT OTH maritime surveillance service in equatorial environment. Our analysis aims to mathematically describe the impact of harsh weather conditions on the performance of the service in order to mitigate it with careful overall system design and provide constant quality of the service. Analyses presented in the paper show that average service latency is about 90 s, but it can rise to about 120 s, which is used as a key information during the sensor data fusion algorithm design. Validity of the analyses is demonstrated through high quality of service with an outage probability of just 0.1% in the driest months up to the 0.7% in the rainiest months. The work presented here can be used as a guideline for deployment of maritime surveillance service solutions in other equatorial regions. Moreover, the gained experience presented in this paper will significantly facilitate future expansions of the existing maritime surveillance network with more HFSWRs. This will be done in such a way that it will not affect the quality of service of the entire system on a large scale.

SL-BiLSTM: A Signal-Based Bidirectional LSTM Network for Over-the-Horizon Target Localization

Deep learning technology provides novel solutions for localization in complex scenarios. Conventional methods generally suffer from performance loss in the long-distance over-the-horizon (OTH) scenario due to uncertain ionospheric conditions. To overcome the adverse effects of the unknown and complex ionosphere on positioning, we propose a deep learning positioning method based on multistation received signals and bidirectional long short-term memory (BiLSTM) network framework (SL-BiLSTM), which refines position information from signal data. Specifically, we first obtain the form of the network input by constructing the received signal model. Second, the proposed method is developed to predict target positions using an SL-BiLSTM network, consisting of three BiLSTM layers, a maxout layer, a fully connected layer, and a regression layer. Then, we discuss two regularization techniques of dropout and randomization which are mainly adopted to prevent network overfitting. Simulations of OTH localization are conducted to examine the performance. The parameters of the network have been trained properly according to the scenario. Finally, the experimental results show that the proposed method can significantly improve the accuracy of OTH positioning at low SNR. When the number of training locations increases to 200, the positioning result of SL-BiLSTM is closest to CRLB at high SNR.

Applying an Adaptive Signal Identification Method to Improve Vessel Echo Detection and Tracking for SeaSonde HF Radar

To enhance remote sensing for maritime safety and security, various sensors need to be integrated into a centralized maritime surveillance system (MSS). High-frequency (HF) radar systems are a type of mainstream technology widely used in international marine remote sensing and have great potential to detect distant sea surface targets due to their over-the-horizon (OTH) capability. However, effectively recognizing targets in spectra with intrinsic strong disturbance echoes and random environmental noise is still challenging. To avoid the above problem, this paper proposes an adaptive signal identification method to detect target signals based on a rapid and flexible threshold. By integrating a watershed segmentation algorithm, the subsequent direction result can be used to automatically compute the direction of arrival (DOA) of the targets. To assist in the orientation of the object, forward intersections are integrated with the technique. Hence, the proposed technique can effectively recognize vessel echoes with automatic identification system (AIS) verification. Experiments have demonstrated the promising feasibility of the proposed method’s performance.

Phase Coherent EM Array Measurements in a Refractive Environment

Phase-coherent measurements of the pilot tone from a digital television (DTV) station were taken by a 24-element vertical array 168 km from the transmitter. Measurements were recorded over 15 days in Southern California, a region known for ducting events in which abnormal atmospheric refractivity patterns allow for the exceptionally long-range propagation of electromagnetic (EM) waves. The DTV station was positioned over the horizon (OTH) relative to the receiver array such that the line of sight was obstructed; thus, significant diffraction loss was expected. Direction-of-arrival (DOA) estimation was performed on the measurements. The measurement campaign objective was to collect the first long-term data set of DOA and the array-signal-to-noise ratio (ASNR) from signals propagating OTH through a refractive channel, toward the goal of enhancing the fidelity of atmospheric refractivity estimates. The analysis of the collected data shows that ASNR is correlated with atmospheric parameters related to refractivity.

Target Bearing Estimation for Ship-Borne HFSWR Using Doppler Effect and Very Small Antenna Array

In this article, a new target bearing angle estimation method for ship-borne high-frequency surface-wave radar (HFSWR) is presented. This new method is designed to give bearing angle estimation of ship targets. It relies on platform motion instead of antenna aperture to acquire bearing angle resolving capability, and hence can be applied to ship-borne HFSWRs that only have very small antenna arrays, and gives small vessels over-the-horizon (OTH) detection capability. This new method requires little modification to existing HFSWR hardware, and only a small amount of additional memory and computing power is needed. Both theoretic analysis and implementation details are given in this article. The new method is tested using real-measured ship-borne HFSWR radar data. The test result proved the effectiveness of the new method.

A High-Frequency Surface Wave Radar Simulation Using FMCW Technique for Ship Detection

Indonesia is an archipelagic country with a vast sea area. This vast sea area becomes a challenge in conducting regional surveillance to maintain maritime conditions. The use of buoys and satellites still has shortcomings in carrying out surveillance despite its excellent surveillance capabilities. A high-frequency radar technology with 3-30 MHz frequency and surface wave propagation are very suitable because it has a radar range that can cross the horizon or commonly refer to as Over the Horizon (OTH). The Frequency Modulated Continuous Wave (FMCW) technique on this radar obtains distance and velocity information by a continuously transmitted frequency modulation. The use of radar in Indonesia for marine surveillance is still infrequent. Therefore, it is relatively difficult to conduct testing and obtain data. In addition, the direct examination requires extended time, so a simulation program is needed. This paper discusses the design of a High-Frequency Surface Wave Radar (HFSWR) simulation program using FMCW modulation technique. The simulation program detected two objects based on time delays due to the distance and velocity of the object with a maximum range of 350 km. It displayed the results in an informative manner. The object detection was based on the results of the Fast Fourier Transform (FFT) from the mixed signals. The mixed signal is a combination of transmitted signal and reflected signal in which there are time delay components due to the object. The simulation program had been tested with input values of distance and velocity that vary, both for one object and two objects, in the radial direction. It generated output that was close to the input value with a level of accuracy of ± 2 km.

Land Suitability Analysis of Over the Horizon Surface Radar for Sea Defense using Geographic Information System

Study of Land suitability using Geographic Information Systems (GIS) is a way to determine the location for many fields, including in the defense field. The Sunda Strait is part of the international shipping route where there are several cases of international smuggling in this region, so that it becomes a concern for Indonesia defense. The concept of marine defense by applying Radar is something must be done at this time. Over The Horizon (OTH) Surface Radar is a type of High-Frequency (HF) radar with a detection distance that goes beyond the earth horizon. Research on OTH Surface Radar Placement is something that can be done at this time, considering Indonesia has not applied it at this time. The method used in this study is to determine the best placement by comparing the parameters of two types of OTH Surface Radar that have been used in other countries to determine the criteria of placement parameters. The analysis process will use the Analysis Hierarchy Process (AHP) by determining the importance of the parameters for OTH Surface Radar Land Suitability. The GIS process is carried out using the Overlay method which is used to determine the suitability based on a matrix of geographic parameters obtained between weight and class. The result is one suitable location to be the main area in the placement of OTH Surface radars for defense in the Sunda Strait located in the district of Pulo Merak, Serang Regency.

A Novel Land-Based High-Frequency Geolocation System

A novel land-based high-frequency (HF) geolocation system is proposed. The geolocating signals are transmitted from the stations with known geographic coordinates. Because of the ionospheric refraction, the signals propagate as skywave in the over-the-horizon (OTH) manner. Therefore, a wide spatial coverage can be achieved. The receiving station uses a small 2-D antenna array to estimate the angle of arrival (AOA) of each transmitter's signal. An intersecting geolocation algorithm based on the geometric relations between the transmitters, and the receiver is described, which only relies on the coordinates of the transmission stations and the azimuth angles of the signals. A novel specific multichannel system structure is also described. It has a simple structure and low hardware cost, as well as good flexibility. The preliminary experimental results prove the feasibility of this geolocation method and its engineering application significance.

Density Based Clustering Data Association Procedure for Real–Time HFSWRs Tracking at OTH Distances

In order to efficiently cover maritime areas at over the horizon (OTH) distances and thus increase marine safety in a nation’s exclusive economic zone (EEZ), a network of maritime sensors built around High Frequency Surface Wave Radars (HFSWR) can be an excellent choice. The critical parameter for success of the deployed sensor network is a real time tracking of all detected vessels. During the tracking process, data association (DA) is the first step and it defines the complexity and thus the speed of the whole tracking process. This paper presents a density based clustering DA procedure where the cluster complexity determines the applied DA procedure within the cluster itself. It is demonstrated that the great majority of clusters (over 98 % of all clusters in the worst case) may be processed in a timely manner with an optimal DA procedure, or more precisely, a Joint Probability Data Association (JPDA). However, a small number of unusually large clusters (less than 2 % of all clusters) requires the application of a sub–optimal DA procedure, more accurately, the Roecker’s suboptimal JPDA algorithm, in order to maintain real time performance of the whole tracking process. Moreover, unlike standard JPDA procedure which tends to be inapplicable for real time tracking in heavily cluttered environment, the density based clustering DA procedure presented here provides real time performances in the very same environment. The whole analysis is done on real HFSWR data obtained from two HFSWR, located in the Gulf of Guinea. The data set used for the experiments includes data obtained during a month and a half of constant HFSWR operation.

A Modified Sequential Multiplexed Method for Detecting Airborne and Sea Targets With Over-the-Horizon Radar

Phased array over-the-horizon (OTH) radar usually needs to detect sea target and airborne target in different directions. Conventionally, the sea target and airborne target are detected sequentially with the coherent integration completely accomplished for each of them. However, the long coherent integration time (CIT) required by the sea target makes the time interval between two airborne target detections too long, which is not conducive to tracking airborne target. To overcome this problem, this paper proposes a new timeframe multiplexing scheme, in which several short-time detections of airborne target are inserted into a long CIT of sea target detection. The proposed scheme seeks to improve the detection frequency of airborne target while ensuring the detection performance of two types of target. However, due to the insertion of airborne target detection, the echo from sea surface is received discontinuously which means that the coherent integration of sea target is incomplete. To tackle it, a recovery algorithm based on the Hankel structured matrix is introduced, which recovers the slow-time domain signal of each range bin and thereby guarantees the detection performance of sea target not damaged. Numerical simulations prove the effectiveness of the proposed algorithm for signal recovery, and also verify that the proposed operating scheme has a shorter time interval for airborne target detection, while the detection performance of two targets are well guaranteed.

Low Cost Antenna Design for the Application of Over the Horizon Surface Wave Radar

The need for surveillance and security in Indonesian water region which can monitor activities of distance object such as illegal fishing, foreign vessels violation, piracy of vessels and smuggling can be done by using radio wave. Maritime radar over the horizon (OTH) surface wave is able to detect the existence of foreign vessels in Indonesian waters. Based on this, the study aimed to design a low cost antenna namely Yagi - Uda linear array antenna at 15 MHz frequency at frequency range 6 – 24 MHz for the application of over the horizon radar. Yagi - Uda antenna is superior in the spread of wave suitable to OTH Radar characteristic over the sea surface and big gain. Yagi - Uda antenna develops rapidly in communication system makes it applied in many modern communication devices nowadays. This antenna was designed and simulated using Simulator Ansoft High Frequency Structure Simulator (HFSS) version 13. The simulation result of the antenna design after doing optimization was return loss (S11) = -29,62 dB, VSWR = 1.068 and gain = 2,413 dBm.

Fuzzy Functional Dependencies as a Method of Choice for Fusion of AIS and OTHR Data.

Maritime situational awareness at over-the-horizon (OTH) distances in exclusive economic zones can be achieved by deploying networks of high-frequency OTH radars (HF-OTHR) in coastal countries along with exploiting automatic identification system (AIS) data. In some regions the reception of AIS messages can be unreliable and with high latency. This leads to difficulties in properly associating AIS data to OTHR tracks. Long history records about the previous whereabouts of vessels based on both OTHR tracks and AIS data can be maintained in order to increase the chances of fusion. If the quantity of data increases significantly, data cleaning can be done in order to minimize system requirements. This process is performed prior to fusing AIS data and observed OTHR tracks. In this paper, we use fuzzy functional dependencies (FFDs) in the context of data fusion from AIS and OTHR sources. The fuzzy logic approach has been shown to be a promising tool for handling data uncertainty from different sensors. The proposed method is experimentally evaluated for fusing AIS data and the target tracks provided by the OTHR installed in the Gulf of Guinea.

Ionospheric Decontamination Method Based on Optimization Criteria in Over-the-Horizon Radar

Over-the-horizon (OTH) radar is important equipment for wide-area surveillance; it has several uses, including aircraft tracking, ship and missile detecting, and remote sensing of the ocean surface. OTH radar uses high frequency electromagnetic wave which propagates by means of refraction within ionosphere; it can provide large range coverage. But this will cause phase contamination due to the unstable movement of the ionosphere. The spectrum of sea clutter and target will be expanded by the ionospheric contamination in the Doppler domain, which will cause the ship target more difficult to separate from the clutter and even buried in the clutter. A new decontamination method is proposed to solve this problem. By analyzing the sea clutter signal model, the proposed method designs an ideal optimized matrix and then uses optimization criteria to estimate phase contamination. Based on the real data, the effectiveness of the new method was validated and compared against other methods.