822 IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, VOL. 9, NO. 5, SEPTEMBER 2012 REMOCEAN: A Flexible X-Band Radar System for Sea-State Monitoring and Surface Current Estimation Francesco Serafino, C. Lugni, G. Ludeno, D. Arturi, M. Uttieri, B. Buonocore, E. Zambianchi, G. Budillon, and F. Soldovieri Abstract—This letter deals with the use of the wave-radar RE- MOCEAN system for sea-state monitoring starting from images collected in the X-band at two different test sites. In particular, the measurement surveys were carried out at two coastal sites in the Gulf of Naples by means of the installation of the radar on a fixed and on a movable platform, respectively. The effectiveness of the system was also tested by means of a comparison between the REMOCEAN results and the high-frequency coastal radar observations, with emphasis to the sea surface current estimation. Index Terms—High-frequency coastal radar, image sequence analysis, marine X-band radar, sea-state monitoring, sea surface current estimation. I. I NTRODUCTION S EA STATE monitoring by X-band radar systems is be- coming increasingly interesting, also due to its spatial resolution, which is much higher than the resolution of the relatively more common high-frequency (HF) coastal radars. In addition, compared to HF radar, X-band radar systems offer an improved operational flexibility; due to their small dimension, low weight, and easy installation, it is possible to install them even on a movable platform and from there to scan the sea surface with high temporal and spatial resolutions [1]–[6]. The operating principle of the X-band radar is based upon backscattering of electromagnetic signals by the sea surface roughness due to the effect of the Bragg resonance [3], [4]: This represent the “useful signal” to be processed when the aim is to achieve a spatial–temporal characterization of the sea state. In this framework, extensive data processing is necessary since modulation effects must be accounted for in the passage from the radar image to the desired spatial–temporal information Manuscript received September 26, 2011; revised November 27, 2011; accepted December 15, 2011. Date of publication February 13, 2012; date of current version May 29, 2012. This work was supported in part by the MED TOSCA project, cofunded by the European Regional Development Fund and by the PROMETEO project, funded by the Campania Region. This work was also supported in part by the project HArBour traffIc opTimizAtion sysTem (HABITAT) under PON “Ricerca e Competitività 2007–2013.” F. Serafino, G. Ludeno, D. Arturi, and F. Soldovieri are with the Institute for Electromagnetic Sensing of the Environment, National Research Coun- cil, 80124 Napoli, Italy (e-mail: serafino.f@irea.cnr.it; ludeno.g@irea.cnr.it; daniele.arturi@libero.it; soldovieri.f@irea.cnr.it). C. Lugni is with the INSEAN, the Italian Ship Model Basin, Department of Seakeeping and Maneuverability, National Research Council, 00128 Roma, Italy (e-mail: c.lugni@insean.it). M. Uttieri, B. Buonocore, E. Zambianchi, and G. Budillon are with the Department of Environmental Sciences (DiSAm), “Parthenope” University, 80143 Napoli, Italy (e-mail: uttieri@uniparthenope.it; berardino.buonocore@ uniparthenope.it; enrico.zambianchi@uniparthenope.it; giorgio.budillon@ uniparthenope.it). Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/LGRS.2011.2182031 about the sea state [3], [7]–[9]. In particular, data processing consists in solving a linear inverse problem where, starting from a series of spatial radar images collected at different time instants, the aim is to determine the elevation η(x, y, t) of the sea surface as a function of the two horizontal spatial variables (related to the sea surface investigated by the radar) and of the time. Here, we present the use of the wave-radar REMOCEAN system for the sea-state parameter estimation at two sites in the Gulf of Naples. In particular, the REMOCEAN system is concerned with the validation of a novel sea surface current estimation, which was numerically shown to achieve better per- formances compared to the least squares (LS)-based approach largely used in the literature [9], [10]. This letter is concerned with two main novel and interesting aspects associated to the presented measurement campaigns. The first one is represented by the use of the X-band radar system in a “mobile data acquisition modality,” which allows to have a great flexibility in the choice of the observation point and is readily installed and operated; this could be of relevant interest in the case of crisis event monitoring and management. The second aspect is the comparison of the wave-radar system results with the information provided by an HF coastal radar operating in the Gulf of Naples [11], [12]. This letter is organized as follows. Section II presents the REMOCEAN system in terms of the technological solutions and the related data processing. Section III summarizes the setup and working principles of the HF coastal radar system. The two measurement campaigns are presented in detail in Section IV, where the results achieved by the REMOCEAN system are compared with the ones obtained by the HF-radar system. Finally, conclusions follow. II. REMOCEAN SYSTEM AND THE DATA PROCESSING This section is devoted to briefly describe the REMOCEAN system by posing attention to both the hardware and the data processing. In particular, we report briefly the data processing approach, already detailed in [9] and [10], with the only aim to make the manuscript fully understandable and self-consistent. The REMOCEAN system hardware consists of a CONSIL- IUM X-band radar radiating a maximum power of 12.5 KW and equipped with a 9-ft (2.74-m)-long antenna (see Fig. 1). The data processing to extract from the X-band radar data the sea-state parameters (such as wave direction, wavelength, period, significant wave height, sea surface current intensity and direction, and temporal–spatial images of the sea surface elevation) is summarized as follows. As a first step, the raw data image sequence is transformed into a 3-D image spectrum by 1545-598X/$31.00 © 2012 IEEE