Sea Surface Reflection Research Articles

Channel Measurements and Characterizations for Long Range Air-to-Ground Communication Systems in the UHF Band

In this paper, we consider long range air-to-ground (AG) communication systems which support aeronautical platforms including unmanned aerial vehicles (UAVs) in the ultra high frequency (UHF) band. For such a system, we present the measurement based path loss analysis and multipath characteristic results at the distance of hundreds of kilometers. To this end, the experimental AG channel measurement system is implemented at the aircraft with various ground station (GS) environments. Through realistic flight tests, we observe the path loss behaviors for long range UHF channels with sea and ground earth surface reflections. By comparing the measurement results with the empirical path loss model and the spherical earth two-ray model, we demonstrate that our measurement results match well with the model. Moreover, for the multipath channel characterization, we provide field test results on the occurrence probability, delay, and power of multipath components in hilly and mountainous environments with various altitudes of the aircraft.

Physics-based modeling of sea clutter phenomenon by a full-wave numerical solver

The sea clutter phenomenon is investigated from a different perspective by using the finite element domain decomposition (FEDD) method, which is a full-wave numerical method based on the decomposition of the problem into sub-problems with the help of the locally-conformal perfectly matched layer (LC-PML) approach. The numerical model developed in this work provides the means to investigate the sea clutter phenomenon by a full-wave Maxwell solver, although the electrical size of computational domain is formidably large. Monte Carlo simulations are performed to obtain some statistical properties of reflectivity. The results are compared with those obtained from existing empirical models and measured data for different polarizations, frequencies, grazing angles and wind speeds (or sea states). It is numerically shown that the probability distribution of the clutter signal power appears to follow the gamma distribution. Furthermore, the concept of ergodicity, which means that the statistical results obtained by ensemble averaging in a single cell are equivalent to those obtained by spatial averaging over a set of consecutive range cells in a radar system, is examined. It is observed from the numerical results that the behavior of the sea clutter random field is consistent with the ergodicity hypothesis. Some conclusions are drawn about the statistical behavior of the sea surface reflectivity.

Wind Direction Retrieval Using Support Vector Machine from CYGNSS Sea Surface Data

In view of the difficulty of wind direction retrieval in the case of the large space and time span of the global sea surface, a method of sea surface wind direction retrieval using a support vector machine (SVM) is proposed. This paper uses the space-borne global navigation satellite systems reflected signal (GNSS-R) as the remote sensing signal source. Using the Cyclone Global Navigation Satellite System (CYGNSS) satellite data, this paper selects a variety of feature parameters according to the correlation between the features of the sea surface reflection signal and the wind direction, including the Delay Doppler Map (DDM), corresponding to the CYGNSS satellite parameters and geometric feature parameters. The Radial Basis Function (RBF) is selected, and parameter optimization is performed through cross-validation based on the grid search method. Finally, the SVM model of sea surface wind direction retrieval is established. The result shows that this method has a high retrieval classification accuracy using the dataset with wind speed greater than 10 m/s, and the root mean square error (RMSE) of the retrieval result is 26.70°.

SNR-Based GNSS-R for Coastal Sea-Level Altimetry

Geodetic Global Navigation Satellite System reflectometry (GNSS-R) uses ground-based signals of opportunity to retrieve sea levels at an intermediate spatial scale. Geodetic GNSS-R is based on the simultaneous reception of Line-of-Sight (LoS) and its coherent GNSS sea surface reflection (non-LOS) signals. The scope of this paper is to present geodetic GNSS-R applied to sea level altimetry. Signal-to-Noise Ratio (SNR) measurements from a Commercial Off-The-Shelf (COTS) geodetic-quality GNSS station at the Haiti Coast Guard Base in Port-au-Prince is used to retrieve sea levels in the International Terrestrial Reference Frame 2014 (ITRF2014). The GNSS-R sea levels are compared with those of the OTT Radar Level Sensor (RLS) installed vertically below the GNSS antenna. The Root-Mean-Square Error (RMSE) between the geodetic GNSS-R sea levels and OTT RLS records is 3.43 cm, with a correlation of 0.96. In addition, the complex differences between the OTT RLS records and 15-min GNSS-R sea levels using Global Positioning System (GPS) and Globalnaya Navigazionnaya Sputnikovaya Sistema (or Global Navigation Satellite System; GLONASS) signals for all the eight major tidal constituents are in mm-level agreement. Therefore, geodetic GNSS-R can be used as a complementary approach to the conventional method for sea level studies in a stable terrestrial reference frame.

Seal bomb explosion sound source characterization.

Small explosive charges, called seal bombs, used by commercial fisheries to deter marine mammals from depredation and accidental bycatch during fishing operations, produce high level sounds that may negatively impact nearby animals. Seal bombs were exploded underwater and recorded at various ranges with a calibrated hydrophone to characterize the pulse waveforms and to provide appropriate propagation loss models for source level (SL) estimates. Waveform refraction became important at about 1500 m slant range with approximately spherical spreading losses observed at shorter ranges. The SL for seal bombs was estimated to be 233 dB re 1 μPa m; however, for impulses such as explosions, better metrics integrate over the pulse duration, accounting for the total energy in the pulse, including source pressure impulse, estimated as 193 Pa m s, and sound exposure source level, estimated as 197 dB re 1 μPa2 m2 s over a 2 ms window. Accounting for the whole 100 ms waveform, including the bubble pulses and sea surface reflections, sound exposure source level was 203 dB re 1 μPa2 m2 s. Furthermore, integrating the energy over an entire event period of multiple explosions (i.e., cumulative sound exposure level) should be considered when evaluating impact.

Sea-surface reflectance factor: replicability of computed values.

The sea-surface reflectance factor ρ required for the determination of the water- leaving radiance from above-water radiometric measurements is derived from radiative transfer simulations relying on models of the sky-radiance distribution and sea-surface statistics. This work primarily investigates the impact on ρ of various sky-radiance and sea-surface models. A specific replicability analysis, restricted to the 550 nm wavelength, has been performed with the Monte Carlo code for Ocean Color Simulations (so-called MOX) accounting for the measurement geometry recommended in protocols for the validation of satellite ocean color data and commonly applied for operational measurements. Results indicate that the variability of ρ increases with wind speed and reaches the largest values for sun elevations close to the zenith or approaching the horizon. In particular, a variability up to about 2% is observed for wind speeds below 4 ms-1 and sun zenith angles larger than 20°. Finally, the benchmark of the ρ values from this study with those formally determined with the Hydrolight code and widely utilized by the ocean color community, exhibits systematic differences. The source of these differences is discussed and the implications for field measurements are addressed.

Modeling propagation in shallow water with the range-dependent sea surfaces and fluid seabeds using the equivalent source method.

This paper describes a shallow water range-dependent propagation model (RPM) based on the equivalent source method (ESM). The proposed model allows both the sea surface and fluid seabed to vary with the propagation range. The proposed equivalent source method-based range-dependent propagation model (ESM-RPM) utilizes three sets of equivalent sources, placed above the sea surface, below the seabed, and above the seabed, which replace the sea surface reflection, seabed reflection, and seabed transmission, respectively. The unknown strengths of the equivalent sources can be determined by solving an inverse problem based on the boundary conditions. The capability of the ESM-RPM for propagation in refractive water is demonstrated by evaluating the Green's function using a modal projection method. Numerical simulations are conducted in iso-velocity and refractive shallow water with an underwater canyon and corrugated surface waves, including two-dimensional (2-D) propagation across the canyon and three-dimensional (3-D) propagation along the canyon. Further simulations demonstrate the 2-D across-canyon and 3-D along-canyon propagations with random rough sea surfaces. The results show that the proposed ESM-RPM provides efficient, benchmark-quality numerical solutions that accurately capture the mode coupling associated with the varying cross section of the waveguide. Thus, the model has great potential to be applied in benchmarking propagation in shallow water with the varying sea surface and seabed.

On the use of the Lloyd's Mirror effect to infer the depth of vocalizing fin whales.

The interference between the direct path and the sea surface reflection of a signal as measured by a receiver is called Lloyd's Mirror effect (LME). It results in a frequency-dependent interference pattern that can be observed in a spectrogram. LME depends on the receiver depth, signal source depth, signal frequency, and slant range between source and receiver. Knowing three of these parameters a priori, LME can be used to estimate the third parameter, such as source depth. Here, the work in Pereira et al. (2016) was expanded to estimate the depth of a vocalizing fin whale recorded by an ocean-bottom seismometer (OBS). In Pereira et al. (2016), the depth of a vocalizing fin whale was inferred by manually comparing spectrograms of LME transmission loss models with observed LME. This study developed an automated procedure to perform the same task using the LME interference pattern observed in the spectrograms of the hydrophone and the vertical channel of the OBS. The results show that the joint use of the two channels was the best approach to estimate a source depth using LME. LME provides a non-intrusive approach for estimating the depth at which a fin whale was vocalizing.

Time Reversal Linearly Constrained Minimum Power Algorithm for Direction of Arrival Estimation in Diffuse Multipath Environments

Direction of arrival (DOA) estimation in diffuse multipath environments is a challenge for ground-based radar remote sensing applications, which has significant value in military fields, such as air defense surveillance. However, radar received echo usually contains various multipath signals caused by the reflection of complex ground or sea surface. With the introduction of multipath signals, traditional algorithms’ performance on angle estimation decreases severely. In response to this problem, the letter proposes a new time reversal (TR) algorithm used for multiple-input multiple-output (MIMO) radar angle estimation. First, the algorithm reconstructs a TR covariance matrix by multiplexing the data’s rows and columns, increasing the estimation accuracy of the TR covariance matrix. Besides, the letter applies a linearly constrained minimum power (LCMP) constraint to suppress diffuse multipath signals according to the prior knowledge of environments. Simulation results examine the improvement of estimation accuracy by the proposed algorithm, also verify the superiority of the proposed algorithm in different multipath scenarios. What’s more, the algorithm has broader applicability due to avoiding the difficulties of removing the coherence and estimating multipath number in practice.

Simultaneous receiver-side deghosting and denoising method based on the sparsity constraint

In marine seismic exploration, the sea surface ghost causes frequency notches and low-frequency loss, which affects the signal-to-noise ratio (SNR) and resolution of seismic records. This paper presents a simultaneous receiver-side deghosting and denoising method based on the sparsity constraint. First, considering the influence of propagation direction and sea surface reflection coefficient, the ghost time delay is calculated accurately, and then the accurate ghost operator is constructed in the frequency—slowness domain. Finally, the ghost-free data are obtained using the sparse constraint algorithm that can effectively suppress the ghost along with the noise energy. This method can remove the ghost and noise simultaneously, achieving quick convergence and with few iterations. It is applied to synthetic data and actual streamer field data. Test results prove that the ghost and notches are suppressed effectively, the SNR is improved, and the band is well broadened.

Error analysis on normal incidence reflectivity measurement and geoacoustic inversion of ocean surficial sediment properties

Normal incidence echo data (bottom reflection) can provide acoustic reflectivity estimates for seabed classification and predicting sediment properties with the use of seabed sediment models. However, the accuracy of normal-incident reflection coefficients significantly affects the geoacoustic inversion result. In this study, a multi-core platform with an acoustic recording system, which can perform a near-scope photographical survey of the seafloor, was used to acquire sound data and collect surficial sediment samples in the southwestern sea off Taiwan. The acquired acoustic data was used to analyze the potential errors in acoustic reflectivity estimation, which were induced by erroneous assumptions in acoustic propagation and sea surface reflection. The subsequent data analysis led to the following conclusions. First, theoretical spherical spreading loss compensation is appropriate in seabed reflection coefficient estimates, and relatively small uncertainties in propagation occur. Second, the assumption of perfect reflection of the sea surface is invalid for seabed reflection coefficient estimates. The resulting errors caused by sea-surface effects are described in detail. Moreover, the collected seabed reflection coefficients were used to invert the sediment properties, which were verified using core samples and camera images.

Polarization Properties of Reflection and Transmission for Oceanographic Lidar Propagating through Rough Sea Surfaces

Over the past few years, oceanographic lidar was applied to many fields, and polarization lidar could provide extra information for marine particles. To retrieve the water properties, many simulation models and inversion methods were developed. However, few of them account for the depolarization effect of a rough sea surface. In this study, we develop a model to calculate reflection and transmission Mueller matrices, coupled with the lidar observation geometry. Compared with another operational method, our model has a satisfactory performance. This model also considers the shadowing effects of wave facets. Then, we analyze the polarized properties in different azimuth and zenith angles and find that the reflection of sea surface has a crucial effect on the polarization properties of lidar. For unpolarized light, the reflected light tends to be partially polarized. However, for lidar light that is completely polarized, there is an obvious depolarization owing to multiple scattering, and the depolarization is not negligible at small incident angles. The retrieval of properties of ocean constituents can be effectively improved, becoming more accurate by accounting for the depolarization effects of sea surfaces based on our method.

Atmospheric Correction of Satellite Ocean Color Remote Sensing in the Presence of High Aerosol Loads

The coverage of valid pixels of remote-sensing reflectance (Rrs) from ocean color imagery is relatively low due to the presence of clouds. In fact, it is also related to the presence of high aerosol optical depth (AOD) and other factors. In order to increase the valid coverage of satellite-retrieved products, a layer removal scheme for atmospheric correction (LRSAC) has been developed to process the ocean color data. The LRSAC used a five-layer structure including atmospheric absorption layer, Rayleigh scattering layer, aerosol scattering layer, sea surface reflection layer, and water-leaving reflectance layer to deal with the relationship of the components of the atmospheric correction. A nonlinear approach was used to solve the multiple reflections of the interface between two adjoining layers and a step-by-step procedure was used to remove effects of each layer. The LRSAC was used to process data from the sea-viewing wide field-of-view sensor (SeaWiFS) and the results were compared with standard products. The average of valid pixels of the global daily Rrs images of the standard products from 1997 to 2010 is only 11.5%, while it reaches up to 30.5% for the LRSAC. This indicates that the LRSAC recovers approximately 1.65 times of invalid pixels as compared with the standard products. Eight-day standard composite images exhibit many large areas with invalid values due to the presence of high AOD, whereas these areas are filled with valid pixels wusing the LRSAC. The ratio image of the mean valid pixel of the LRSAC to that of the standard products indicates that the number of valid pixels of the LRSAC increases with an increase of AOD. The LRSAC can increase the number of valid pixels by more than two times in about 33.8% of ocean areas with high AOD values. The accuracy of Rrs from the LRSAC was validated using the following two in situ datasets: the Marine Optical BuoY (MOBY) and the NASA bio-Optical Marine Algorithm Dataset (NOMAD). Most matchup pairs are distributed around the 1:1 line indicating that the systematic bias of the LRSAC is relatively small. The global mean relative error (MRE) of Rrs is 7.9% and the root mean square error (RMSE) is 0.00099 sr−1 for the MOBY matchups. Similarly, the MRE and RMSE are 2.1% and 0.0025 sr−1 for the NOMAD matchups, respectively. The accuracy of LRSAC was also evaluated by different groups of matchups according to the increase of AOD values, indicating that the errors of Rrs were little affected by the presence of high AOD values. Therefore, the LRSAC can significantly improve the coverage of valid pixels of Rrs with a similar accuracy in the presence of high AOD.

Sea-Ice Concentration Derived From GNSS Reflection Measurements in Fram Strait

Reflection power derived from the global navigation satellite system (GNSS) observations and its sensitivity to sea-ice concentration are investigated in this article. A corresponding experiment has been conducted during the Fram Strait cruise of the Norwegian research vessel Lance in summer 2016. The dedicated setup with a GNSS Occultation Reflectometry Scatterometry (GORS) receiver and dual-polarization (left- and right-handed) antenna links recorded 1922 h of reflection events during the 20-day cruise of the ship. The antenna setup, mounted 25.0 m above the waterline, serves to acquire sea surface reflections at grazing angles below 30°. Within a 5-min coherent integration period, direct and reflected signal contributions can be separated. Except for the highest sea states, with roll angle changes of 20° peak to peak, the separation allows to retrieve the reflection power and quantifies it in cross-, co-, and cross-to-co-polar ratios. The sea-ice concentration is inverted from power ratios using a non-linear least-squares algorithm. Additional data on sea-ice concentration gathered by a watchman on the ship are used for validation. The inversion results have a 20% resolution in concentration and 3-h resolution in time. The validation shows that the cross- and cross-to-co-polar data are sensitive to the sea-ice concentration. The respective Pearson correlation of 0.75 and 0.67 further suggests studies to foster the application of the GNSS data for sea-ice reflectometry.

Modeling the Chlorophyll-a from Sea Surface Reflectance in West Africa by Deep Learning Methods: A Comparison of Multiple Algorithms

Deep learning provide successful applications in many fields. Recently, machines learning are involved for oceans remote sensing applications. In this study, we use and compare about eight (8) deep learning estimators for retrieval of a mainly pigment of phytoplankton. Depending on the water case and the multiple instruments simultaneouslyobserving the earth on a variety of platforms, several algorithm are used to estimate the chlolophyll-a from marine reflectance. By using a long-term multi-sensor time-series of satellite ocean-colour data, as MODIS, SeaWifs, VIIRS, MERIS, etc, we make a unique deep network model able to establish a relationship between sea surface reflectance and chlorophyll-a from any measurement satellite sensor over West Africa. These data fusion take into account the bias between case water and instruments. We construct several chlorophyll-a concentration prediction deep learning based models, compare them and therefore use the best for our study. Results obtained for accuracy training and test are quite good. The mean absolute error are very low and vary between 0,07 to 0,13 mg/m3.

Low-Velocity Small Target Detection With Doppler-Guided Retrospective Filter in High-Resolution Radar at Fast Scan Mode

It is a difficult task for high-resolution maritime radars operating at a fast scan mode to find sea-surface floating and low-velocity small targets due to ubiquitous sea clutter, sporadic sea spikes like target returns, and shortage of shared database. In this paper, a simulation method is presented to generate high-resolution radar returns of a local sea surface with a structural trend in texture and sea spikes by integrating the existing results on large-scale sea surface generation, sea surface reflectivity, Doppler characteristics of sea clutter, and properties of sea spikes. Generally, sea-surface small target detection at a fast scan mode is composed of intrascan integration to suppress sea clutter and interscan integration to exclude false alarms and sea spikes. Based on the Doppler difference between targets and sea clutter at the two time scales of a coherent processing interval (CPI) of tens of milliseconds and a scan period of several seconds, a Doppler-guided retrospective filter (DGRF) detector is proposed, which uses the optimum coherent detection in intrascan integration and a DGRF in interscan binary and test statistic integrations. The two integrations and Doppler consistency of integrated plots are fused for the final decision. Owing to the Doppler guidance, the proposed detector effectively impedes the integration of false alarms of the intrascan processing and provides significant detection performance improvement, which is verified by the simulated data and real radar data with test small targets.

Feature identification using acoustic signature of Ocean Researcher III (ORIII) of Taiwan

Feature identification using acoustic signature of Ocean Researcher III (ORIII) of Taiwan

Prediction of signatures of airgun arrays using dual near‐field hydrophones

ABSTRACTSuccessful estimation of airgun‐array signatures from near‐field measurements depends on the accuracy of poorly controlled model parameters such as the effective sea surface reflection coefficient and source depth. We propose a method for prediction of robust source signatures, which are insensitive to fluctuations of the latter parameters. The method uses vertical pairs of near‐field hydrophones to measure near‐field pressure and its vertical gradient, combination of which eliminates sea surface reflections from the near‐field data. This excludes the uncertainty related to the fluctuating sea state and source depth from the process of inversion of the near‐field data for source signature. The method explicitly separates the recorded near‐field pressure into its up and down going components, which allows one to measure the effective frequency‐ and angle‐dependent sea surface reflection coefficient right at the source, as well as to estimate the actual source depth. Tests on synthetic and field data demonstrate robust performance of the method.

HF Sky wave hop-propagation on earth’s surfaces in different conditions

HF Radio waves can be reflected by the ionosphere and the earth’s surface and propagate long distance from the transmitter to the receiver with several hops, which is also called sky wave propagation. Path loss of sky wave propagation varies with different conditions of ionosphere and types of the earth’s surfaces. In order to get a deeper insight into the multi-hop sky wave propagation, we establish a model to investigate calculate the propagation losses under certain circumstances. We separate the path loss into three parts, namely the free space propagation loss (FSPL), the ionosphere propagation loss (IPL) and the sea surface reflection loss (SSRL). The FSPL and the IPL are calculated by using the propagation loss equations from ITU (International Telecommunication Union) standard. The SSRL is estimated by Pierson-Moscowitz (PM) sea wave spectrum and Kirchhoff approximation (KA) method. The model results agree well with the existing observations that the strength of the reflection off the turbulent ocean attenuates more than that of the clam ocean.

Characterization of radiance from the ocean surface by hyperspectral imaging.

A novel snapshot hyperspectral imager is introduced for ocean color (OC) applications and its capabilities are demonstrated. The instrument provides hyperspectral radiance images with a wide field-of-view (FOV) and short exposure time, which is valuable for the direct characterization of the wind-roughened surface in various illumination conditions and wind speeds. Uncertainties in the total(Lt), sky (Ls) and derived water-leaving (Lw)radiances at viewing angles of 20-60° are determined as a function of wind speed together with associated correlation coefficients and variances of the sea surface reflectance coefficient ρ. Estimated Lw uncertainties can partially explain the inaccuracy of satellite retrievals in the blue bands in the coastal waters. It is shown that in above-water measurements in no-glint conditions with viewing and azimuth angles of 40° and 90°, respectively, for both Lt(λ) and Ls(λ) the impact of FOV is minimal at least up to measured W = 5.7 m/s for full-angle FOV of 4° and larger. Implications of uncertainties for the derivation of water leaving radiance in above-water ship-borne and AERONET-OC measurements are discussed.