First-Order Ocean Surface Cross Section for Shipborne Bistatic HFSWR: Derivation and Simulation

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

In high-frequency surface wave radar (HFSWR) systems, clutter is a common phenomenon that causes objects to be submerged. Space-time adaptive processing (STAP), which uses two-dimensional data to increase the degrees of freedom, has recently become a crucial tool for clutter suppression in advanced HFSWR systems. However, in STAP, the pattern is distorted if a clutter component is contained in the main lobe, which leads to errors in estimating the target angle and Doppler frequency. To solve the main-lobe distortion problem, this study developed a clutter-suppression method based on beam reshaping (BR). In this method, clutter components were estimated and maximally suppressed in the side lobe while ensuring that the main lobe remained intact. The results of the proposed algorithm were evaluated by comparison with those of standard STAP and sparse-representation STAP (SR-STAP). Among the tested algorithms, the proposed BR algorithm had the best suppression performance and the most accurate main-lobe peak response, thereby preserving the target angle and Doppler frequency information. The BR algorithm can assist with target detection and tracking despite a background with ionospheric clutter.

Accurate azimuth detection of targets in High Frequency Surface Wave Radars in an essential task of the primary signal processing in order to determine target locations. In the presence of strong interference, it becomes more difficult and represents an important challenge because it can degrade the radar's performance. In this paper, we propose an improved method for high-resolution azimuth detection in such systems under strong external interference which manifests itself as a grouping of false targets by azimuth. The paper contains the detailed method description, the description of the proposed method for improved azimuth detection and the performance analysis based on the experimentally obtained radar data. The results show that it is possible to achieve significant improvements in the detectability of targets.

High frequency (HF) interference in surface wave over-the-horizon (OTH) radars typically exhibits a time-varying or non-stationary spatial structure. Adaptive beamformers that update the spatial filtering weight vector within the coherent processing interval (CPI) are likely to suppress such interference most effectively, but the intra-CPI antenna pattern fluctuations result in temporal de-correlation of the clutter which severely degrades sub-clutter visibility after Doppler processing. A robust adaptive beamformer that effectively suppresses non-stationary interference without degrading sub-clutter visibility is proposed. The new algorithm is computationally efficient and suitable for practical implementation. Its operational performance is evaluated using experimental data recorded by the Iluka HF surface wave (HFSW) OTH radar, located near Darwin in far north Australia.