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At the Helmholtz Zentrum Geesthacht (HZG), Germany an oceanic monitoring system, based on a Dopplerized microwave radar was developed. Within this paper we present the capabilities of this system to measure ocean surface wave properties such as significant wave height, peak wave period, peak wave lengths as well as other spectral wave parameters. In addition, the system is able to detect wave breaking, shear stress of the wind field, near-surface currents, and the bathymetry in shallow water areas. Because of the diversity of measurement capabilities, the system particularly well suited for monitoring and investigation of hydrographic and oceanographic process.

This work compares the spectral analysis of ocean wave fields performed from nautical radar and waverider buoy measurements. The data were taken by a radar station located in the northern coast of Spain and by a buoy that was moored close to the area covered by the radar for its calibration. In this area the sea states are mainly dominated by the presence of northwest swells coming from storms originating in the North Atlantic Ocean. In this order, the radar calibration and the comparisons of different spectral parameters and scalar spectra from both sensors are presented.

Nautical radar and scalar buoy measurements of ocean wind generated waves have been analysed to compare the spectral parameters estimated from both sensors. The time series of different sea-state parameters and the differences and ratios of the values obtained from radar and buoy data using different analysis methods are compared. It has been observed that main differences between the sea-state parameters derived by using measurements obtained from both sensors result both from device characteristics and from the method of spectral estimation. In particular, it is shown that the Nyquist frequency has an important effect on the value of the sea-state parameters depending on spectral moments of order higher than zero.

The objective of the EuroROSE (European Radar Ocean Sensing) project was to combine area covering ground-based remote-sensed wave and current data with high-resolution numerical forecast models to provide nowcasts and forecasts for coastal marine operators. Two experiments to test and to demonstrate the system took place: one on the coast of Norway, north of Bergen in March 2000 and the second on the north coast of Spain at Gijon in October–November 2000. Qualitative and quantitative intercomparisons of the wave measurements and wave model products from these experiments are presented. These include measurements using the Wellen Radar (WERA) high-frequency (HF) radar, the WaMoS (Wave Monitoring System) X-band radar, a directional Waverider and output from the WAM wave model. Comparisons are made of the full directional spectra and of various derived parameters. This is the first-ever intercomparison between HF and X-band radar wave measurements and between either of these and WAM. It has provided a data set covering a much wider range of storm and swell conditions than had been available previously for radar wave-measurement validation purposes and has clarified a number of limitations of the radars as well as providing a lot of very useful radar wave data for future model-validation applications. The intercomparison has led to improvements in the data quality control procedures of both WaMoS and WERA. The two radar sytems measured significant wave height with mean biases of 3% and 6%, respectively, and mean direction differences of less than 2° in both cases. Limitations in the WAM model implementation are also discussed.

The aim of this work is to present an approach to describe complex sea states including the ones consisting of superpositions of swell and wind sea components, using a nautical radar in X-band as a remote sensing technique. In the present article, the inversion method to obtain the spectral representation of the wave fields is described. The method is applied to analyse data obtained from simulation techniques, as well as from measurements obtained during oceanographic campaigns in the Bay of Biscay and North Sea.

This work studies wave groupiness properties in the spatiotemporal domain of wind-generated waves. For that purpose, analysis of temporal sequences of X-band radar images of the sea surface acquired at grazing incidence conditions is carrying out. The results presented in this work are based on the estimation of the local and instantaneous envelope of the sea surface derived from the radar data. The data shown in the paper were acquired from two different X-band radar stations, one located in the North Sea and the other station in the coast of New Zealand.

The presence of sea clutter in marine radar signals is sometimes not desired. So, efficient radar signal processing techniques are needed to reduce it. In this way, nonlinear signal processing techniques based on neural networks (NNs) are used in the proposed clutter reduction system. The developed experiments show promising results characterized by different subjective (visual analysis of the processed radar images) and objective (clutter reduction, target enhancement and signal-to-clutter ratio improvement) criteria. Moreover, a deep study of the NN structure is done, where the low computational cost and the high processing speed of the proposed NN structure are emphasized.

This work presents a method to filter sea clutter features for radar images acquired from ordinary marine radar sensors, which are incoherent radars working in X-band and horizontal polarization. The proposed method considers short temporal sequences of consecutive sea clutter images. This method is based on the acquired experience about the spectral structure of the sea clutter obtained from the use of marine radars to detect ocean wave fields and the related sea state parameters.

This paper presents the remote sensing techniques of measuring sea states, currents and bathymetry by using an X-band nautical radar. It briefly describes the fundamental methods to infer sea state information (e.g. ocean wave and current parameters) from nautical radar imagery. In addition, this work describes in detail the performance of the Wave Monitoring System WaMoS II (a commercial system for real-time monitoring of wave fields based on nautical radar technology). Two examples of nautical radar applications are presented: the first application is an example of the standard WaMoS II installation for sea state measurements, and the second application shows results of a research project aiming at the determination of shallow water bathymetry by means of nautical radar imagery.

Recent techniques to derive sea state parameters in the spatial domain from radar images of the sea surface have been derived. This work describes these techniques in order to derive wave elevation maps from space borne SAR and nautical radar images of the sea surface. These wave elevation maps permits to extract additional sea state information in the spatial domain derived from the statistical analysis of the wave elevation, as well as wave height, spatial distribution.

The objective of the EuroROSE project was to combine area covering ground-based remote-sensed wave and current data with high resolution numerical forecast models to provide now- and forecasts for coastal marine operators. The first experiment to test and demonstrate the system took place on the coast of Norway, north of Bergen in March 2000. Qualitative and quantitative intercomparisons of the wave measurements and wave model products from this experiment are presented. These include measurements using the WERA HF radar, the WaMoS X-band radar, a directional waverider and output from the WAM wave model. Comparisons are made of the full directional spectra and of various derived parameters. This is the first ever intercomparison between HF and X-band radar wave measurements and between either of these and WAM.

This study presents a novel way for detecting ships in sea clutter. For this purpose, the information contained in the Radar images obtained by an incoherent X-band maritime Radar is used. The ship detection is solved by feedforward artificial neural networks, such as the multilayer perceptrons (MLPs). In a first approach, the MLP processes the information extracted from the Radar images using the commonly used horizontal and vertical selection templates. But, if a suitable combination of these selection templates is done, better detection performances are achieved. So, two improved selection templates are proposed, which are based on cross and plus shapes. All these templates are also applied in a commonly used detector taken as reference, the CA-CFAR detector. Its performance is compared with the one achieved by the proposed detector. This comparison shows how the MLP-based detector outperforms the CA-CFAR detector in all the cases under study. The results are presented in terms of objective (probabilities of false alarm and detection) and subjective estimations of their performances. The improved MLP-based detector also presents low computational cost and high robustness in its performance against changes in the sea conditions and ship properties.

The European Radar Ocean Sensing (EuroROSE) project is presented. The project was designed to monitor and forecast sea state conditions in coastal areas, in particular port approaches. The aim was to provide area-covering information to traffic managers and search and rescue organizations, using ground based radar and numerical models in combination with data assimilation techniques.