Bayesian Estimator Based Target Localization in Ship Monitoring System Using Multiple Compact High Frequency Surface Wave Radars

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.

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.

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.

This paper proposes a new method to estimate the target altitude of an aircraft using high frequency surface wave radar(HFSWR) for the surveillance of the Exclusive Economic Zone. The initial position and velocity in 3-D coordinates are estimated based on quasi-Newton method from a sequence of measurements, this initial values are incorporated for 3-D tracking with the modified iterated extended Kalman filter(IEKF), a multiple model approach is adopted to improve the tracking accuracy. The simulation results demonstrate the effectiveness of the proposed method.

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.

Assessment of actual detection capabilities obtained with high frequency surface wave radar (HFSWR) is a key issue for the global surveillance of the exclusive economic zone (EEZ). ONERA (The French Aerospace Lab) has just finished a ten month trial cycle of its new full digital HFSWR system. This system uses digital signal generation, digital receivers, high computational power workstations and low power transmitters. All results extracted from the trial database are compliant with the theory in particular concerning sea clutter and ionospheric clutter. Moreover, the detection of vessels up to 170 km and aircrafts up to 75 km (results obtained with cooperative targets and ground truth data) shows the over the horizon capabilities of the system. Finally, clutter reduction prospects are also presented.

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.

Surveillance of the large Exclusive Economic Zone (i.e. 200 NM from the shore lines) is a challenge since many years. Three main issues are recurrently pointed out: the radar coverage up to the EEZ boundaries, the monitoring of small vessels and the analysis of the vessel behaviors. The European project I2C (i.e. Integrated System for Interoperable sensors & Information sources for Common abnormal vessel behaviour detection & Collaborative identification of threat) tackles those three issues and supply an effective solution from detection up to threat identification. The present paper focuses on long range detection with the new High Frequency Surface Wave Radar (HFSWR), owned by ONERA, which supplies the EEZ coverage to I2C project.

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.

Land-based High Frequency (HF) surface wave radars have become an effective tool for sensing currents, winds and waves, and many types of HF radars are in operation around the world. Being different from land-based HF radars, this paper proposes a concept of shore-to-air bistatic HF radar for ocean observation. The configuration of shore-to-air bistatic HF radar is introduced in the paper, and the first-order scattering model is also presented. The paper studies and analyzes the average scattered cross section per unit area at different operating frequencies and with various wind speeds via simulation. Simulations demonstrate that the average scattered cross section per unit area varies along with frequency, wind speed and scattering direction. The proposed model will help develop shore-to-air bistatic HF radars for ocean observation.

Direct target localization and vector-velocity measurement method based on bandwidth synthesis in distributed high frequency surface wave radar

The increasing use of High Frequency Surface Wave Radar (HFSWR) for the surveillance of coastal regions is faced with the problem of limited channel availability in the electromagnetic spectrum. Thus, there is a need for multiple radars to share a common frequency channel. Proof-of-concept work is presented here for a method to operate multiple radar systems on a common carrier frequency. A review is provided of an existing concept where a common waveform is modulated by tones varying by a few hertz across the different radars. The signals from the different radars are separated by either pulse-domain filtering or Doppler processing. An experiment has been performed that demonstrates the feasibility of the method. Limitations of the method are considered in terms of the linearity of the propagation channel.

The detection performance of high frequency surface wave radar is impacted by the ionospheric clutter. In order to suppress the ionospheric clutter, it is important to research the physical mechanism of ionosphere. In this paper, it is demonstrated, convincingly for the first time, the chaotic dynamics of the ionospheric clutter. The results are obtained using the actual data collected from a series of experiments in Weihai Radar Station, China. The study includes the stationarity and nonlinearity test, phase-space reconstruction, correlation dimension analysis and Lyapunov exponents analysis. And finally, it is found that ionospheric clutter in HFSWR is a chaotic dynamical process with relatively few degrees of freedom, in contrast to the stochastic approach where the ionospheric clutter is viewed as a random process with a large number of degrees of freedom[1]. Also, this new approach will further provide an original way to analyse the ionospheric clutter suppression method.

Shore-based high frequency surface wave radars (HFSWR) have been used to monitor large areas of the coastal ocean, and there continues to be an increase in their use for estimation of marine environmental features associated with currents, waves and winds. Recently, interest has been generated in mounting the transmitting (TX) or receiving antennas (RX), or both, on ocean platforms. This provides new challenges as the motion induced in the antennas influences the phasing of the transmitted and received electric fields. Here, the development of a first-order cross section of the ocean which incorporates the effects of antenna motion is outlined.