Portable High Frequency Surface Wave Radar OSMAR-S

Based on the scattering mechanism between HF radio wave and sea surface, the key issues of inversing wind direction from the first-order oceanic backscatter of HF Surface Wave Radar(HFSWR) were researched, and an algorithm has been applied to the HFSWR data. Firstly, the foundational theory of inversing wind direction was discussed based on the first-order radar cross section equation. Secondly, the basic requirements of inversing wind direction were derived by the well-generated wave spectral model. Thirdly, the typical Longuet-Higgins and Donelan wind directional models were discussed and the appropriate directional spreading parameters were determined by both dogvane measured and HFSWR data. Finally, the algorithm was applied to the measured Doppler sea echo data. Seen from the results, the inversed wind direction shows good agreement with the measured wind direction of dogvane, and the wind direction ambiguity is almost eliminated. Therefore the algorithm turns out to be effective.

A bistatic high-frequency surface wave radar (HFSWR) with both receiving and transmitting stations placed on different ships (platforms) is a new radar system and referred to as shipborne bistatic HFSWR. In this paper, a first-order ocean surface cross section of shipborne bistatic HFSWR was derived. The first-order cross-section models for three different cases, i.e., ships moving with uniform, periodic, and hybrid motion states, respectively, are presented. The corresponding first-order Doppler spectra were simulated, and the spread width of the first-order spectrum was investigated. The simulation results show that the characteristics of the first-order spectrum are similar to those of a shore-based bistatic HFSWR when the transmitting and receiving platforms move in opposite directions. The first-order spectral spread width in the case of platforms with opposite directions is much smaller than that in the case of platforms with the same direction. This finding is useful for reducing HFSWR first-order spectrum spread due to platform motion, thus improving the target detection performance of the shipborne bistatic HFSWR. In addition, periodic oscillation motion of both platforms will cause complex motion-induced peaks in the first-order spectrum, which may be detrimental to target detection and ocean remote sensing. These results have important implications for the application of shipborne bistatic HFSWR.

The electromagnetic waves emitted by high- frequency surface wave radar (HFSWR) propagate forward in the form of ground waves. After being scattered by the detection target, the back-scattering field is still transmitted back to the HFSWR by ground wave propagation. The characteristics of propagation have important influences on the detection capability of the HFSWR. In this paper, the electric field integral equation (EFIE) of ground wave propagation on undulating earth would be solved by iterative method to obtain the numerical solution of ground wave propagation. The solution process is verified by compared with the classical theory of Fock ground wave diffraction on smooth spherical ground. Then the altitude profile data of different terrains are extracted by using Google Earth and Global Mapper, and the attenuation characteristics of high-frequency ground wave propagation under the actual propagation path conditions are calculated. The influence of ground fluctuation on ground wave propagation is analyzed.

Doppler frequencies generated by the navigating ship targets may coincide with the first order Doppler spectrum of the sea clutter in high frequency surface wave radar (HFSWR). Therefore, the ship targets fall in this clutter spectrum were usually undetectable by the traditional processing method in HFSWR. In this paper, we introduced a spatial blind filtering method based on oblique projection, which utilized the characteristic difference of ship target and sea clutter returns in spatial directions. Different from the broad beam pattern formed by the conventional digital beamforming technique, the method proposed realized clutter suppressing within the broad beam when the notches are sufficiently dense by blind filtering. The ship target in sea clutter was detected in filed data processing results of HFSWR and it was further verified by the synchronous automatic identification system (AIS) information collected. Those demonstrated that our method can detect the ship targets in sea clutter and this spatial blind filtering technique had a great potential in solving this problem in HFSWR.

Due to the incapability of high frequency surface wave radar (HFSWR) to detect undercurrent parameters, a new algorithm is proposed to apply a three-dimensional (3D) nonlinear barotropic shallow sea and continental shelf model in coordinate system to the inversion of undercurrent. The calculation domain of this model is the area detected by HFSWR. Considering the benthal topography of the detected area and the ocean dynamic parameters, such as surface current, wind and wave detected by HFSWR, the relation between surface current and undercurrent is established in this model. Accordingly, the undercurrent parameters of corresponding area are obtained. The inversion results agree with the law of ocean dynamics and reproduce the movement of undercurrent.

A bistatic/monostatic HF surface wave radar (HFSWR) experiment was conducted using both the transmit and receive systems of the HFSWR at Cape Race, Newfoundland and the receive system of the HFSWR at Cape Bonavista, Newfoundland. While the HFSWR at Cape Race operated in the monostatic mode, the transmitter at Cape Race and the receiver at Cape Bonavista were synchronized via the Global Positioning System to operate in the bistatic mode. The results of the experiment show that the range of the clutter return from a specified layer in the ionosphere in the bistatic radar, and the range of the clutter return from the same layer in the monostatic radar follow, approximately, the relationship specified by the Pythagorean theorem, i.e., R=(h/sup 2/+(L/2)/sup 2/)/sup 1/2/, where h is the virtual height of the specified layer in the ionosphere, which is also the range of the clutter return in the monostatic radar case, and L is the separation between the transmitter and receiver in the bistatic configuration. Based on these observations, we calculated the coverage areas of bistatic HFSWR systems for water-entry areas along coastlines. The calculation shows that a bistatic HFSWR system has the potential to significantly improve the nighttime coverage area over a monostatic system, while, approximately, maintaining the same daytime coverage.

Marine Operations such as pipe laying, subsea installations, heavy lifting operations, work-over operations, crane operations are extremely sensitive to metocean conditions. Wind, wave and currents from different directions and long period wave motion can cause adverse vessel response which may impair operations. Thus, without systematic sea state monitoring, marine operations sensitive to wind, wave height, wave period and vessel motion can be subject to delays, cost overruns, safety issues, and asset damage. Precise knowledge of the sea state during such operations is an essential requirement which has become more critical as offshore activities have moved into ever greater water depths, and into hostile frontier areas. This calls for a reliable and accurate on-board system for continuous, real-time wave and motion monitoring and recording.

High frequency surface wave radar (HFSWR) is becoming accepted as an important remote sensing device for sea state monitoring, and the frequency-modulated continuous wave (FMCW) has been widely used as the radar transmitted waveform. However, the performance of HFSWR may be significantly impacted by unwanted echoes, of which ionospheric clutter is one of the main sources. During transmission, a portion of the radar radiation may travel upwards to the ionosphere from the transmitting antenna. This may be partially reflected back to the receiving antennas directly or via the ocean surface, the latter being refered to as ionosphere-ocean propagation. The purpose of this paper is to investigate the physical mechanism of how the ionosphere clutter might be analytically characterized within the radar backscatter spectrum. The first-order HF radar clutter power and its radar cross section of ionosphere-ocean propagation for an FMCW source will be derived theoretically, and then simulated and compared for a variety of ionosphere velocities and wavelengths.

In many applications, the interacting multiple model (IMM) estimator provides better performance over the single model Kalman filter (KF). However, there are two high frequency surface wave radar (HFSWR) factors which seem to make the IMM estimator less attractive: Firstly, the radar has a very long integration time, up to a few hundred seconds for ship detection; Secondly, the radar has very limited detection capability of maneuvering targets. It is unknown whether the IMM estimator will perform better over an EKF for real time HFSWR. The purpose of this paper is to compare the EKF with the IMM estimator. An optimal noise level and critical value have been found for HFSWR EKF design. The results demonstrated that the IMM estimator does not yield improved performance.

This paper demonstrates the benefits that high-frequency surface wave radars (HFSWR) are bringing to maritime safety and security in off-shore activities at over the horizon distances. As a primary means for remote sensing of marine and maritime environment, a network of HFSWRs is deployed in the western part of the Gulf of Guinea and covers an area of over 100 km2. Alongside HFSWRs, usual maritime sensors are utilized for vessel tracking as well, however, only satellite automatic identification systems (SAIS) and land automatic identification systems (LAIS) are capable of covering over the horizon distances. Unfortunately, both LAIS and SAIS require vessel cooperation in order to provide any data, which is often abused by vessels conducting illegal activities. Here, analysis is done in which AIS and HFSWR data are compared in order to identify a pattern of behavior of non–cooperative vessels (vessels with onboard AIS devices turned off) so a proper risk assessment may be achieved. It is shown that typical patterns can be easily recognized for two illegal activities which plague the waters where this study is conducted. Those illegal activities are oil bunkering and piracy, both conducted off-shore and out of the reach of the usual coastal sensors such as X or S band radars. Furthermore, tracks created whilst conducting illegal activities are easily distinguishable from others in the overall operational picture. Additionally, it should be pointed out that numerous vessels are switching off their AIS devices when they leave the coastal regions in order to avoid detection by pirate vessels. This behavior can also be easily recognized and must not be mixed with the illegal activities mentioned above.

Virtual aperture extension of small aperture array has attracted wide attention in high‐frequency surface wave radar (HFSWR). A biologically inspired coupled (BIC) system is employed to virtually extend the array aperture. However, the existing researches on BIC only consider the array signal processing model and do not combine it with actual radar signal principle. To indeed apply the BIC system to HFSWR, two detailed methods which combine the BIC and HFSWR at signal level are proposed. A three‐dimensional signal model of HFSWR considering array processing was established and the entire signal processing was derived. Then, two combination methods, namely fast‐time domain (FTD)‐BIC and slow‐time domain (STD)‐BIC are proposed. The former implements the BIC before fast‐time processing, while the latter implements the BIC before slow‐time processing. The authors demonstrate that they can virtually extend the array aperture without affecting the target detection. Meanwhile, their capabilities in multi‐target scenarios are analysed and satisfactory conclusions are obtained. By numerical simulations and experiments, the array aperture and range‐Doppler (RD) spectrum of the standard HFSWR and BIC‐HFSWR are compared. The results show that while the performance of their RD spectrum is almost the same, BIC‐HFSWR has an enlarged virtual aperture than standard HFSWR.

Sea clutter has a major impact on the detection performance of a shipborne high-frequency surface wave radar (HFSWR) system. Due to the platform motion of shipborne HFSWR, the Doppler spectrum of the first-order sea clutter suffers from some broadening so that the targets submerged in this broadening Doppler spectrum can be hardly detected. In this letter, an improved oblique projection (IOP) method, combining the oblique projection (OP) algorithm and the method of sea clutter suppression in the Doppler domain, is proposed to suppress sea clutter in both Doppler domain and spatial domain for shipborne HFSWR. Compared with the OP and the orthogonal weighting algorithms, the proposed IOP algorithm is shown to give far superior suppression results in the Doppler domain and can achieve better azimuth estimation results based on real data.

Land or sea clutter Doppler frequency shift and spectrum spread are traditionally attributed to the radar platform motion relative to the clutter scatterer. However, another spreading mechanism of the clutter Doppler spectrum exists in onshore bistatic high frequency surface wave radar (HFSWR), which is presented in this study. Based on the space-time distribution of the first-order sea clutter in onshore bistatic HFSWR, the spreading model is proposed, which is verified by the simulation and experimental results. It demonstrates that the space-time model would be of fundamental importance to the future experimental investigations, not only of target detection but also of ocean remote sensing with onshore bistatic HFSWR.

Because of the complexity of the marine environment, the High Frequency Surface Wave Radar (HFSWR) in dealing with marine information will be accompanied by a lot of interference and noise. To solve this problem, first of all, we use the logic method to measure the trace information of the radar in order to find out the logical starting track. Secondly, the Kalman filter is used to predict and calculate the trajectory based on the existing starting track. So as to realize the purpose of finding the track in the complex HFSWR track signal. In this paper, The data comes from HFSWR data and Automatic Identification System (AIS) data on China's Bohai Bay. Finally, in order to show the accuracy of the method, the HFSWR track results calculated by the method used in this paper are compared with the track results of AIS.

Recently, the usage of high frequency surface wave radars has been expanded to monitoring of ships within observable region because it can always observe wide target region with low power consumption. However, ship monitoring systems using high frequency radars suffer from the fact that a detection position is far away from true position. To resolve this problem, the proposed method determines final location by applying Bayesian estimator to detection results from each ship monitoring system in high frequency radar network. According to Bayesian theory, a posterior distribution is factorized into likelihood and prior distributions, and both distributions are modeled by using each detection results and auto-identification system data, respectively. Effectiveness of the proposed method is demonstrated through appropriate synthetic and real data. From the results, location accuracy can be improved when the proposed method is applied to location estimation.