Simulation analysis of first order sea clutter spectrum for shipborne bistatic HFSWR

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.

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.

This paper proposes a bistatic High Frequency Surface Wave Radar (HFSWR) system for ocean current mapping. This system is composed of two remote sites. Both receive backscattered echoes as well as bistatic echoes transmitted by the other. An experiment was conducted on the coast of the North China Sea during January 2010, which proved effectiveness of the radar system.

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 broadening first-order sea clutters caused by the signals from different directions with various radial current velocities create severe disturbance for target detection using high-frequency surface wave radar (HFSWR). Conventional sea clutter suppression methods tend to remove the sea clutter and target signals when they are mixed in the Doppler spectrum. Based on the characteristics of the target signal and sea clutter in spatial–temporal domain, a new first-order sea clutter suppression method for HFSWR using orthogonal projection is proposed. The proposed method uses the data from multichannels and slow-time domain at the adjacent range cell to construct a covariance matrix, which can be used to obtain the sea clutter subspace by eigendecomposition. Later, original signals are projected onto the sea clutter subspace. Finally, subtract the component of the original signals in the sea clutter subspace from the original signals to achieve the suppression of sea clutter by retaining the target signals. The simulation and experimental results for a single target and multiple targets cases indicate that the proposed method can suppress the first-order sea clutter effectively, which enhances the target detection capacity in the sea clutter zone for 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.

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.

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.

In high frequency surface wave radar (HFSWR), Doppler frequencies of the vessels targets may overlap the first order Doppler frequencies from the sea clutter interference. Therefor it is hard to discover the vessel targets and estimate direction of arrive (DOA) of the ship targets. In this paper, the target direction finding method based on fractional Fourier transform (FRFT) was introduced for uniform acceleration/deceleration target, which used the frequency peculiarity difference between the targets and the first order sea clutter. Before the target DOA estimation, sea clutter were suppressed by FRFT method. The effectiveness of the method was verified by the simulations. The result demonstrated our method can estimate the DOA of targets in first order Doppler spectrum of sea clutter.

This letter proposes using the 2-D multiple-signal classification (MUSIC) based on sparse recovery (SR) to improve the target-detection capability of high-frequency surface wave radar (HFSWR). Usually, for wide-beam HFSWRs, target detection is first conducted in the range-Doppler spectrum, and bearings are then estimated by superresolution methods such as MUSIC. Unfortunately, the conventional cascaded method can easily result in unfavorable deterioration of multitarget detection when different target signals tend to become mixed in the Doppler spectrum. Moreover, sea clutter is an unwanted signal that frequently masks target signals. To enhance the detection of multiple targets and targets embedded in sea clutter, spatial-temporal joint estimation has been proposed. However, because of the lack of spatial-temporal snapshots caused by the nonstationarity of target signals, the efficiency of the estimator cannot be guaranteed. To overcome this shortcoming, multiple-measurement-vector-based SR, which has been used to solve many under-sampling problems in the past ten years, is adopted. Our approach can effectively detect a target embedded in sea clutter as well as multiple adjacent targets and distinguish them from each other. Results obtained using real data with opportunistic targets validate our approach. Therefore, the proposed 2-D SR-MUSIC approach improves target detection and outperforms conventional cascaded methods.

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.

Sea clutter has a serious influence on the detection performance of a shipborne high‐frequency surface wave radar (HFSWR) system, especially when the target is submerged in the spread Doppler spectrum of the first‐order sea clutter. A prediction cancellation (PC) method based on the radial basis function neural network (RBFNN) is put forward to suppress the first‐order sea clutter in time domain for shipborne HFSWR. Using the RBFNN trained by the averaged sea clutter data from the range cells surrounding the range cell of interest, the PC algorithm is implemented in the interested range cell. Compared with the two‐dimensional fast Fourier transformation plus digital beam forming algorithm, the proposed PC algorithm is shown to give far superior sea clutter suppression results based on real data.

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.

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.

This paper studies the Arctic ionospheric environment using ionosonde data and assesses the potential of high-frequency surface-wave radar (HFSWR) surveillance for surface vessels and low-altitute air targets. The evaluation is based on sporadic-E (Es) interference in the HFSWR signal. For surveillance problems up to 150 km, such as in the Northwest Passage through Canada's Arctic islands, the ionospheric Es clutter is the dominant clutter that may degrade the performance of the future HFSWR systems. The results show that Es occurs least often at Eureka in winter and at Resolute Bay in summer. Generally, Es occurs less often in the Arctic than at midlatitudes. Observations also suggest that the best time to perform HFSWR surveillance in the Arctic is between approximately 07:00-15:00 UT and 21:00-24:00 UT. During these hours, the number of days that Es interference occurs in a month and the range of frequencies (in the 4-7 MHz range) reflected are minimized compared to other times of the day. These observations suggest that the future HFSWR systems in the Northwest Passage should be designed to operate at higher radio frequencies. For example, a radio frequency higher than 7 MHz can be operated in order to minimize the Es interference during the hours of 07:00-15:00 UT and 21:00-24:00 UT. It is concluded that the Es interference in the HFSWR signal in the Arctic can be equal to or less than that at midlatitudes (e.g., off the east coast of Newfoundland). Furthermore, the overall performance of HFSWR will be better in the Arctic than at midlatitudes due to lower levels of interference of sea clutter and man-made-related noises combined with a much better level of HFSWR propagation.