KEYWORDS: Interferometry, Interference (communication), Receivers, Statistical analysis, Signal to noise ratio, Acoustics, Signal processing, Statistical modeling, Data communications, Sensors
Current sonar and radar applications use interferometry to estimate the arrival angles of backscattered signals at
time-sampling rate. This direction-finding method is based on a phase-difference measurement between two close
receivers. To quantify the associated bathymetric measurement quality, it is necessary to model the statistical
properties of the interferometric-phase estimator. Thus, this paper investigates the received signal structure,
decomposing it into three different terms: a part correlated on the two receivers, an uncorrelated part and an
ambient noise term.
This paper shows that the uncorrelated part and the noise term can be merged into a unique, random term
damaging the measurement performance. Concerning the correlated part, its modulus can be modeled either as
a random or a constant variable according to the type of underwater acoustic application. The existence of these
two statistical behaviors is verified on real data collected from different underwater scenarios such as a horizontal
emitter-receiver communication and a bathymetric seafloor survey. The physical understood of the resulting
phase distributions makes it possible to model and simulate the interferometric-signal variance (associated with
the measurement accuracy) according to the underwater applications through simple hypotheses.
Concerning bathymetric multibeam echosondeur systems, the interferometric technique is widely used to get the altitude of an illuminated seafloor section beam. Classical methods only use the zero crossing instant of phase difference to obtain the sea depth. Nevertheless, the phase difference gives more information near the zero crossing. Using the idea of radar multilook, the seabed footprints of two close beams overlap and, consequently, it exists a common illuminated area. In this paper, we show that the mutual information between the two close beams is enough to merge them into one because of the coherently processing of the signals received from multiple sensors (that is, beamforming). This mutual information, set up by several beamforming methods, makes possible to take into account all points included in the beam footprint in order to rebuild more accurately the sea floor. Besides, considering a beamforming width between ±25° and ±60°, we can recreate a continuous phase difference by merging all phase differences. Beam angles close to nadir will not be considered because of their non acceptable performance in terms of interferometric quality. In addition, the effect of changing the interferometric spacing, commonly called baseline, is also studied. A correct baseline value plays an important role in high-resolution beamforming. Actually, the influence of the multibaseline causes an increase of the phase difference variance, and therefore, an increase of the measurement errors. Finally, we propose the fusion of the multilook techniques and the baseline effects to improve the multibeam
echosondeur bottom detection.
In sonar imaging for seafloor remote sensing, research activities are more and more oriented on the use of data fusion approaches. Nowadays, it is well established that using sonar images, the Digital Elevation Maps (DEMs), can be generated by exploiting either the amplitude information or the phase information of the acoustic signal. In this paper, the main interest consists on the generation of a complete Digital Elevation Map (DEM) by the use of a data fusion approach of two existing DEMs issued from two different techniques. The aim of the proposed approach is to elaborate a general interpretation system that coherently links works on data selection and fusion leading to improve DEMs generation and to exploit it in the seafloor remote sensing applications (particularly for the inhomogeneous scenes with a variety terrain). In this paper, shape from shading and the interferometry techniques are considered. Then, the manner of the DEMs fusion proposed, has been based on fuzzy logic and some fuzzy propositions, which defined using experts a priori knowledge source. This promising idea enables information to be managed through the consideration of the imprecision and ambiguity information and the benefit provide by the injection of the a priori knowledge in the decision taken system.
This paper concerns the possibilities that side scan sonar have to determine the bathymetry. New side scan sonars, which are able to image the sea bottom with a high definition, estimate the relief with the same definition as conventional sonar images, using an interferometric multisensors system. Drawbacks concern the accuracy and errors of the numerical altitude model. Interferometric methods use a phase difference to determine a time delay between two sensors. The phase difference belongs to a finite interval (-π, +π), but the time delay between two sensors does not belong to a finite interval: the phase is 2π biased. The used sonar is designend for the use of the vernier technique, which allows to remove this bias. The difficulty comes from interferometric noise, which generates errors on the 2π bias estimation derived from the verier. The traditional way to reduce noise impact on the interferometric signal, is to average data. This method does not preserve the resolution of the bathymetric estimation. This paper presents an attempt to improve the accuracy and resolution of the interferometric signal through a wavelets based method of image despecklization. Traditionally, despecklization is processed on the logarithm of absolute value of the signal. But for this application, the proposed interferometric despecklizaiotn is achieved directly on the interferometric signal by integrating information, guided by the despeckled image. Finally, this multiscale analysis corresponds to an auto adaptive average filtering. A variant of this method is introduced and based on this assumption. This method used the identify function to reconstruct the signal. On the presented results, phase despecklization improves considerably the quality of the interferometric signal in terms of to noise ratio, without an important degradation of resolution.
KEYWORDS: Interferometry, Image fusion, Sensors, Electronic filtering, Data fusion, Signal to noise ratio, Image filtering, Wavefronts, Signal processing, Gaussian filters
This paper concerns the possibilities of sea bottom imaging and altitude determining of each imaged point. The performances of new side scan sonars which are able to image the sea bottom with a high definition and are able to evaluate the relief with the same definition derive from an interferometric multisensor system. The drawbacks concern the precision of the numerical altitude model. One way to improve the measurements precision is to merge all the information issued from the multi-sensors system. This leads to increase the Signal to Noise Ratio (SNR) and the robustness of the used method. The aim of this paper is to clearly demonstrate the ability to derive benefits of all information issued from the three arrays side scan sonar by merging: (1) the three phase signals obtained at the output of the sensors, (2) this same set of data after the application of different processing methods, and (3) the a priori relief contextual information. The key idea the proposed fusion technique is to exploit the strength and the weaknesses of each data element in the fusion of process so that the global SNR will be improved as well as the robustness to hostile noisy environments.
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