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In this paper the uncertainty evaluation of the recently proposed Unified Method for Thermo-Electric Module characterization is carried out. The measurement model is detailed and individual uncertainty contributions are highlighted, with close reference to the instrumentation and measurement setup. The uncertainty evaluation is performed by means of a Monte Carlo Simulation. The same algorithm is used to perform a sensitivity analysis, giving a comprehensive insight into the most critical issues of the proposed method and assessing the performance of the two adopted electrical stimuli. The experimental results thereby obtained are discussed and improvements to the measurement setup and technique are finally proposed.

In this paper, we present an efficient technique to compensate the dynamic offset error in the voltamperometric method, for the subhertz characterization of hysteretic magnetic materials. The integration of the output voltage at the secondary winding inherently tends to cumulate the residual offset voltage that is not constant over long experiments as often supposed. Slight variations of the residual offset voltage due to multiple effects make simple linear detrend techniques ineffective and limit the achievable accuracy up to make useless the obtained data. We first use custom signals to identify the thermal and electrical dynamic models of the measurement setup, and further we remove the model-based expected trends. The results confirm the effectiveness of the proposed method for error compensation, with accuracy improvements up to 40 dB.

In this paper the modeling and the design of a microwave sensor is proposed for real-time fuel quality monitoring, with particular regard to water-in-fuel measurement. A mechanical and fluid-dynamic design has been performed, evaluating the stiffness, the robustness of the sensor structure and the pressure field acting on it. Furthermore, an electromagnetic study has been carried out to verify the validity of the physical measurement principle. The adopted procedure involves the modeling of the sensor in CAD and the simulation of its behavior. The sensor, based on microwave transmittance, is attractive because of its simplicity and foreseeable low cost.

In this paper an integrated system (hardware and software), named GeoLab, for geotechnical measurement on submarine contaminated sediments is described; GeoLab permits to reduce the probability of human mistakes often made during long and repetitive manual operations and, to increase speed, accuracy, and productivity in geotechnical laboratory tests. A new, suitable management software was developed to permit the communication with different data acquisition platforms and to easily adapt software in case of changes in the laboratory procedures.

This work deals with a useful PID control scheme to impose a user defined temperature gradient on a Thermoelectric heater used as heat source for Thermoelectric Generators characterization. These devices used in both power supply and cooler/heater configurations are one of the most promising to provide electricity and heat to spacecraft and instruments or for sensor nodes self-powered from small temperature gradient, such as temperature variations available internally and externally throughout the human body. During the experiments, the room temperature was imposed by a thermal chamber while the heater was driven by an opportunely amplified PWM signal generated by an Arduino UNO board on which the PID controller is implemented. The whole process is supervised by a LabVIEW virtual instrument which permits the bidirectional communication and the report to users.

This paper explores the use of a microwave-reflectometry- based system for the automatic control and real-time monitoring of the flow and of the liquid level in intravenous (IV) medical infusions. In medical and hospital contexts, other kinds of devices, mainly based on the optical detection and counting of the infusion drops, are used. Nevertheless, the proposed system is aimed at circumventing some typical drawbacks deriving from the adoption of these traditional methods, thus allowing an efficient alternative for automatically monitoring the instantaneous flow of IV medical solutions. To this purpose, the proposed system combines microwave time-domain reflectometry (TDR) measurements with a noninvasive sensing element (i.e., strip electrodes directly attached to the external surface of the infusion bottle). Experimental results confirm that, by using low-cost portable TDR devices, the solution flow process can be controlled with acceptable accuracy. Therefore, the proposed method can be regarded as a promising control tool for in-hospital patient management as well as for telemedicine programs.

Several monitoring methods, in the recent years, involved microwave/radio frequency (RF) reflectometry techniques, particularly in remote sensing, environmental and industrial application fields. The main advantages using reflectometry are due to its relevant performance characteristics, in terms of high flexibility, high sensitivity and large application conditions. Furthermore, the time domain reflectometry (TDR) presents some attractive advantages, related to the possible determination of the spatial location and nature of various objects, in real-time and with a non-destructive approach. This makes the TDR technique an appealing candidate for a variety of environmental and industrial applications. Although TDR instruments are commonly used today, particularly for the above mentioned purposes, the state of the art is rather lacking in liquid monitoring applications. In this paper we demonstrate that a suitable combination of TDR detecting functionalities, in terms of spatial localization, dielectric properties estimation and coaxial probe performance characteristics, leads to an enhanced quantitative and qualitative monitoring method. Really, in one shot, the analysis of TDR data allows the measurement of liquid levels, the determination of multiple interfaces in layered media, as well as the evaluation of dielectric properties, such as dielectric permittivity or electrical conductivity. Moreover, some applications to real cases are proposed, referred to petrol–chemical mixtures or water-based liquids, thus validating the approach on a wide range of materials.

Time-domain reflectometry (TDR) based on instruments are commonly used for several monitoring methods, particularly in soil moisture and volumetric water-content evaluation. Furthermore, significant advantages of TDR methodology, mostly related to the possible determination in real-time and to a nondestructive approach of the spatial location and nature of various objects, make this technique an appealing candidate for a variety of environmental and industrial applications. In this paper, we show that the suitable combination of TDR-detecting functionalities can lead to a joint quantitative and qualitative monitoring method for liquid-control purposes, so that, in one shot, the analysis of TDR data allow the measurement of liquid levels, the determination of multiple interfaces in layered media, as well as the evaluation of dielectric properties, thus opening challenging perspectives for several monitoring applications, particularly in fluid-processing-related industry. For such purposes, a detailed analysis of the uncertainty of the proposed measurement method is mandatory; hence, a metrological characterization of the method is carried out, demonstrating that the presented technique is definitely valid for simultaneously measuring levels and dielectric constants of liquids, with uncertainties under 2%. Results obtained for different liquid samples validate the approach on a wide range of dielectric materials and demonstrate the robustness and reliability of the proposed TDR technique.

Time-domain-reflectometry (TDR) measurements, which were originally used to locate and diagnose faults in transmission lines, have been widely applied in geology and soil science for accurate and flexible measurements of soil moisture and water content. Furthermore, the most attractive advantages of TDR rely on the possible determination of the spatial location and nature of various objects, both in real time and with a nondestructive approach. This makes the TDR technique an appealing candidate for a variety of environmental and industrial applications. Although the TDR instruments are commonly used to date, particularly for the aforementioned purposes, the state of the art is rather lacking in liquid-monitoring applications. This paper describes how the suitable combination of TDR detecting functionalities can lead to a simultaneous monitoring of quantitative and qualitative properties of liquid samples. In fact, the proposed TDR method allows, in one shot, the measurement of liquid levels, the determination of multiple interfaces in layered media, and the evaluation of dielectric properties such as dielectric permittivity or electrical conductivity. Some applications to real cases are proposed, which are referred to petrol–chemical mixtures or water-based liquids, thus validating the approach on a wide range of materials.

Permittivity monitoring for quality control in fluid-related industrial applications requires difficult procedures and the process control frequently limits the use of traditional sensing technologies. In this paper is reported a combined approach, based on time-domain reflectometry (TDR) and frequency-domain analysis, in order to appropriately improve the measurement of the frequency-dependent dielectric characteristics over a wide range of fluid materials, even when lossy liquids are involved. For this purpose, we have developed a robust algorithm for the time-to-frequency-domain dielectric characterization that suitably compensates the error contribution caused by several effects such as signal dissipation, multiple reflections, impedance mismatching, time-domain truncation and data fitting procedure. In order to assess the combined approach in the time and frequency domain, experimental measurements have been made with both a TDR and vector network analyser (VNA), using the same probe system. Results obtained through the use of such an algorithm on TDR data have been compared with those directly measured in the frequency domain by the VNA, and good agreement has been observed. Substantial improvements are attained in accuracy, high sensitivity and flexibility of the detection method and, most importantly, in the possibility of using low-cost instrumentation directly operating in the time domain.

The paper presents an overview on the problem of waveform recorder characterization, stressing the opportunity of working out a standard for the model identification of a recorder. As a concrete contribution to this project, the authors propose a unified complete behavioral model for single-channel data acquisition systems, discuss the suitability of known test methods for its identification, and draw some guidelines for the construction of a complete identification procedure.

During the last years, many algorithms have been performed which are suitable both to increase the accuracy of estimating techniques in the frequency domain, and the precision and dynamic performance of digital instrumentation affected by a white quantization noise source. However, in the estimation of the power spectral density (PSD) function of a stationary random process through digital techniques, there is still one major drawback due to the trade-off between bias and variance, which the user should control. The performance of the periodogram estimator can be improved by averaging or smoothing the estimates, in the frequency domain, of nonoverlapping sections of the data sample but, for a finite sample size, we cannot completely control both bias and variance; when we attempt to reduce one, the other one increases. The main aim of this paper is to show how the estimation accuracy of a smoothed periodogram can be improved by adopting flat-top tapering in conjunction with averaging of 75% overlapped time slices of the data sample, based on Welch's method. The expressions for both components—those due to variance and bias—of the global (rms) amplitude estimation error have been derived and a lot of comparisons with the accuracy level given by classical cosine windows are proposed in order to confirm the better behaviour of the preoposed measurement technique. It has been developed and optimized to be very useful for control, diagnostics (ATE) and monitoring of electrical and electronic systems, under noisy non-sinusoidal conditions.

In previous works, the authors have explored the use of a microwave reflectometry-based system for the automatic control and real-time monitoring of the flow and of the liquid level in intravenous medical infusions. In this paper, the repeatability of the measurements obtained with the proposed method is evaluated, by employing an ad-hoc experimental procedure. Preliminary results demonstrate that the method shows a good repeatability; nevertheless, there are still some issues that should be solved. © 2012 IEEE.

This article explores the use of a microwave reflectometry-based system for the automatic control and real-time monitoring of the flow and of the liquid level in intravenous medical infusions. In medical and hospital contexts other kind of devices, mainly based on the optical detection and counting of the infusion drops, are used. Nevertheless, the proposed system is aimed at circumventing some typical drawbacks deriving from the optical sensing, thus allowing an efficient alternative solution for automatically monitoring the instantaneous flow of intravenous medical solutions. To this purpose, the proposed system combines microwave time domain reflectometry (TDR) measurements with a non-invasive sensing element (i.e.: strip electrodes directly attached to the external surface of the infusion bottle). Experimental results confirm that, by using low-cost portable TDR devices, the solution flow process can be accurately controlled. Therefore the proposed method can be successfully adopted as a promising control tool for in-hospital patient management as well as for telemedicine programs.

In this paper a model based approach is adopted to estimate the thoracic volume. A cylindrical model is developed and standard relations of cylinder are used for the volumetric computations. Six normal male subjects are registered for the analysis and validation of the cylindrical model. Anthropometric dimensions and thoracic impedances are measured as input parameters. Appreciable rhythmic variations of thoracic impedances with computed thoracic volumes are observed for all the registered subjects. The observation can be utilized for monitoring and diagnosis of various respiratory and pulmonary disorders.

Photovoltaic modules need recognized and validated measurements through appropriate certification in order to be sold and used in diverse applications. Certification process, that includes measurements and characterization, is an important aspect of photovoltaic issues. This paper presents an improved intercomparison method of characterizing Photovoltaic Modules (PVMs) in outdoor conditions and in short observation time. The key output is energy prediction.

Electronic knee is new opportunity for people having one or two amputated legs. Differently from traditional prosthesis, electronic knee is the first one to be driven by a microprocessor with an hydraulic control for the static and dynamic steps. It is become a positive key issue for the comfort and movement freedom for transfemoral amputed people. Despite the use of microprocessor, many difficulties arise during connection on human being and from calibration. This paper presents a technique of predicting calibration operations and stabilometric measurements in order to allow a better connection between electronic knee and the amputated patient. The technique is based on a novel genetic doped algorithm capable of producing the postural positions and correct calibration.

Epilepsy is one of the most common neurological disorders, affecting around 1 in 200 of the population. However, identifying epilepsy can be difficult because seizures tend to be relatively infrequent events and an electroencephalogram (EEG) does not always show abnormalities. The aim of this project is to develop a new methods that could improve the diagnosis of epilepsy, leading to earlier treatment and to a better quality of life for epileptic patients. The above methods must be composed with a flexible hardware development in order to discriminate noise and bad signals from correct EEG, MEG (Magnetoencephalogram), Eye Image recognition, Somnography and DTI (Diffusion Tensor Imaging). Even if there are EEG signal classifiers, it is suitable to perform a correct signal processing according to particular clinical reference, that is, it is difficult to have a classifier for all circumstances but it is possible to adapt EEG processing on current patient. Preliminary results are described for processing biomedical signals, namely EEG signals, in order to train the adaptive filtering in recognizing and choosing correct frequencies at which it is possible to reduce noise.

Breathing plays a key role in human health, especially in terms of fatigue and energy. Oxygen maximum consumption is important for lung. Lung functional performance is characterized by: its ventilator capacity, to bring air (thus O 2 ) into alveoli, and its capacity to transfer O 2 and CO 2 into and from the pulmonary capillary bed. Hence, the O 2 and CO 2 diffusion coefficients as well as the O 2 consumption rate and the CO 2 production rate represent the lung performance indices. Both gases have a relevant importance in human body energy expenditure; one of the best instrumentation used for this purpose is ergospirometer. It allows to know the oxygen maximum consumption or the aerobic maximum power VO 2 , that is the maximum amount of energy (moles of ATP) produced by different substances (carbohydrates, lipids and proteins) per unit of time. This research proposes a signal processing approach for improving the quality of data recovered from the ergospirometric sessions. The ergospirometric is used to evaluate the efficiency of walking for two main reasons: rehabilitation and cough impact on a patient before a surgery. Cough can be an index of muscular and lung problems on human body. Before a surgery, it could be necessary to discriminate some pathologies in presence of cough. The results offered by the research are characterized by a good accuracy and they help clinicians in knowing precised values of oxygen maximum consumption, hence, human body expenditure. A Cosmed K4b2, as ergospirometer, is used in this research. It is located at Research Institute

Photovoltaic panels (PVs) are growing in terms of development and utilization all over the world. Different manufacturers deliver photovoltaic panel characteristics according to the locations where they are tested. Since there are different technological materials used in the manufacturing of PVs, the present research represents an effective method of prediction of the energy produced by the photovoltaic systems and an acceptable method of their characterization by using an experimental setup. The prediction of the energy produced by a photovoltaic system is generally made through software which uses algorithms that describe the trend of the efficiency of the panels depending on the temperature, the radiation and, in more particular cases, depending on the incident spectrum features.

Kriging code is a regression method used in the context of the space analysis (geostatistics) which allows to interpolate a quantity in the space, minimizing the mean square error. In the statistics context it is better well known as gaussian process. Knowing the value of a quantity in a few points in the space (for example the temperature taken in every town of an area), we can determine the quantity value in other points for which measurements do not exist, for example a resort of campaign unequipped of thermometer. This paper shows the study of the development of a Kriging code for the treatment of environmental and electrical parameters for photovoltaic panels. This method will be tested through a case of study realized by us.

An efficient and portable photoacoustic multi-gas monitor for biomedical application is needed in hospital in order to detect indoor gas pollution, r to protect the health of workers, patients and visitors. If the highest precision is not required, especially for continuous monitoring of anaesthetic gases, a LED-based (light emitting diode) detecting system can be employed in order to estimate an attention threshold level of gas. This paper illustrates a design and characterization of a led-based photoacoustic chamber (sensing-actuating system and cell) for anaesthetic gas detection. A measurement campaign has been conducted in a surgery room; the results have been compared with another photoacoustic instrumentation used simultaneously. The main asset of the new system is a double source of LED light instead of a more traditional system.

Pipeline monitoring plays a key role in many industrial processes and human activities, in particular, for the management of water resources. Spectral analysis response, used for leak detection, is generally based on fast Fourier transform (FFT). The aim of this paper is to develop an alternative method based on filter diagonalization method (FDM), mainly used in nuclear magnetic resonance, in order to overcome limitations of FFT approach. Thanks to its robustness, FDM allows difficulties created by zigzag pipeline, buried water tubes and in general by the presence of noisily boundary conditions to be solved. Moreover, another objective is reached by reducing FFT recovery error for narrow pipelines. An experimental facility has been constructed to show the results of this alternative approach.

Energy harvesting from human body has been undergoing an interesting and quick development thanks to the technological availability of new electronic components and the growing of different applications, in particular, for biomedical and social impacts on human beings' daily life. The main scope of this paper is to modeling and to design a thermoelectric generator that extracts energy from human tissue warmth in order to supply a biomedical hearing prosthesis for death persons. An array of sensors based on thermocouple effect has been used. A conditioning and accumulator circuitry has been designed and tested

There is a strong urge for methodologies for leak detection in pipelines and location that are quick and require less costly instrumentation. Moreover they should not cause the cessation of pipeline operation, and not require that the whole network be surveyed by trained personnel; leak detection methodologies based on transient analysis can achieve these goals. Basing the reflexion according to fast detecting systems, spectral analysis response is a topic of interest. Among spectral analysis response techniques, FFT (Fast Fourier Transform) and wavelets are included. Different other techniques are utilized but they are costly and difficult to be used. The research proposes the use of FFT for smaller and zigzag pipelines by overcoming limitations encountered in current scientific literature. The developed improvements, used for pipeline section small than 20 cm, permit to prevent, with interesting accuracy, the leakage.

Leak detection and control for pipelines is an important aspect for managing economic key issues, namely, saving water in urban water distribution network, protecting oil pipelines and allowing a correct conveying of harmful and toxic fluids. Basing the reflexion according to fast detecting systems, spectral analysis response is a topic of interest. Among spectral analysis response techniques, FFT (Fast Fourier Transform) is rated. Different other techniques are utilized but they are costly and difficult to be used. The research proposes the use of FFT for smaller pipelines by overcoming limitations encountered in current scientific literature. The developed improvements, used for pipeline section small than 20 cm, permit to detect and to prevent leaks with less accuracy, the leakage.

Electronic component improvements allow everyone to use them for performing new features in different applications. Lidar signal control is matter of continuous design and it can be studied in order to increase signal-to-noise ratio. Fortunately, the advent, of programmable gain amplifiers, switching capacitor filters and specific AD converters, is the stimulus of improving lidar signal quality. The main scope of this paper is to design and to realize a hardware simulator capable of reproducing the behavior of lidar signal control. This paper aims at describing the results of an automatic control system for Raman lidar signals. The system is based on the following units: laser source, damper, PMT (Photomultiplier), current - to - voltage converter, switched capacitor filter, programmable gain amplifier, A/D converter and FIR filter. This configuration allows the use of FIR filter that is not strictly necessary but it can help in adapting signal according to the amplitude. One of the main advantage of this system is to obtain a flexible and programmable board.

Beamforming is one of the ultimate opportunity to improve distance systems in order to detect punctual and widespread obstacles. Distance ranging for mobile and fixed systems, namely, cars, vehicles, vessels and airplanes, is a key issue for nowadays demands. Distance between cars and from obstacles can be established and measured using laser and ultrasound. Cloudy and foggy conditions are utmost requirements for testing distance ranging facilities. If based on ultrasound, they can be easily integrated by a sophisticated on-board software in order to perform new features. This paper introduces interesting aspects of defining new requirements for an acoustic imaging capable of reconstructing obstacle features by targeting it using a special array of sensors.

An efficient and portable photoacoustic multi-gas monitor for biomedical application is needed in hospital in order to protect the health of workers, patients and, somewhat, visitors. If highest precision is not required, especially for continuous monitoring of anaesthetic gases, a LED (light emitting diode) based-detecting system can be employed in order to estimate an attention threshold level of gas. But when a gas purification facility is used in order to exhaust biomedical gas present in a surgery room, it can be suitable to employ a different sensing technology to reduce costs and to increase efficiency, since the quality and the quantity of gases decrease, a new affordable instrumentation based on LED technology is proposed in the present research. The idea behind this work is to control LED sources by a cheaper system in other to get acceptable results that are valid for an interesting range of frequencies. Particular care has been given to conditioning subsystem because of mixing RGB colours.

Traffic congestion is a severe problem on European freeways. According to a study of the European Commission, its impact will increase even up to 10% in the year 2010. Since building new infrastructure is no longer an appropriate option in most (Western) countries, there are many approaches towards a more effective road usage and a more ‘intelligent’ way of increasing the capacity of the road network. Examples of advanced traffic control systems are, e.g., ‘intelligent’ speed limits, adaptive ramp metering, or dynamic routing. This paper focuses on a proposal of a vehicle acoustic imaging that allows driver to recognize obstacles and other cars around him in a safe way. The proposed front end electronic and sensing system are included in a specific architecture supervised by a microcontroller. The used algorithm for gathering data belongs to LCMV and LCMP beamforming methods.

EEG signals reveal interesting information about human being's cerebral activity. Nowadays information contents can help physicians especially in rehabilitation operations, that is, it is possible to design specific biomedical experimentation in order to help patients to retrieve acceptable and good conditions of their physical apparatus or specific areas of them. In this paper, preliminary criteria of designing and implementing an EEG classification are proposed. A modeling of classification rules is also described.

Epilepsy is one of the most common neurological disorders, affecting around 1 in 200 of the population. However, identifying epilepsy can be difficult because seizures tend to be relatively infrequent events and an electroencephalogram (EEG) does not always show abnormalities. The aim of this project is to develop a new methods that could improve the diagnosis of epilepsy, leading to earlier treatment and to a better quality of life for epileptic patients. The above methods must be composed with a flexible hardware development in order to discriminate noise and had signals from correct EEG, MEG (Magnetoencephalogram) and Eye Image recognition. Even if there are EEG signal classifiers, it is suitable to perform a correct signal processing according to particular clinical reference, that is, it is difficult to have a classifier for all circumstances but it is possible to adapt EEG processing on current patient. This paper deals with a new approach of developing an architecture with a an embedded coding included in a framework agreement between University and IRCCS "E. Medea".

Digital components and architecture offer more flexibility in lieu of analog ones. This asset allows designers to improve electronic equipment and instrumentation behaviour. Lidar processing systems can be improved through new components and architecture, particularly in data collection, acquisition and processing. This paper presents criteria and implementation of an electronic unit capable of substituting Raman lidar - based discriminator and multichannel scaler. For this experiment, a Hamamatsu H7732P-01 photomultiplier has been used.

A Nuclear Magnetic Resonance (NMR) instrumentation is a complex apparatus that uses a magnetic field generated by a permanent magnet, gradient of magnetic field generated by coil and radiofrequency signal. The above set must be synchronized in order to produce images of MRI (Magnetic Resonance Imaging). The aim of this paper is to describe an implementation of an interface that allows a severe protection of NMR instrumentation from data troubleshoots and network failures. A control protocol has been developed and an electronic card has been also realized in laboratory.

Time domain reflectometry (TDR) technique is widely used in hydrology and soil science for accurate and flexible soil water content measurements. The most attractive advantages concerning the considered TDR measurement system are: good precision and accuracy, high reliability of the measuring head, a unique approach of pulsing a long coaxial probe and analysing the reflected voltage signature caused by changes in impedance, capability of multiplexing several probes, possibility of remotely acceding, controlling and electronically retrieving and transmitting data through existing telecommunication technologies. A time domain reflectometer transmits the incident signal, an ultra short rise time (200 ps), step voltage pulse, along the transmission line and records the travel time and the magnitude of all reflected signals (echo) returning from the controlled system. Changes in impedance (capacitance, inductance and resistance) causing electromagnetic discontinuities that reflect voltage can be located, particularly, for liquid level and dielectric properties monitoring purposes. The above mentioned discontinuities result from impedance changes produced by changes in the dielectric constant. The time domain reflectometry method used in this research has the purpose to monitor the behavior of different liquid substances, detecting their levels and giving information about their characteristics, such as volumetric content, dielectric constant, electrical conductivity, as well as the identification of different interfaces. Furthermore, the main objective of the present work is to develop an interpretation method for the analysis of TDR signal that, associated with a simple calibration procedure and with a suitable probe design can ensure, at the same time, quantitative and qualitative liquid monitoring

Two techniques for accurate harmonic analysis of industrial power systems are presented. The first is based on the fast Fourier transform (FFT) of the sampling sequences of voltage and current waveforms. It performs a decimation of the acquired data, adopting nonrecursive low-pass FIR filters, to achieve frequency zooming in the spectrum. Then, a flat-top windowing is executed to reduce the negative effects of leakage and interference phenomena. The second technique is based on the extended Kalman filter (EKF) theory. It permits online identification of the instantaneous values of the fundamental and harmonic contents. It also gives the r.m.s. harmonic contents and the total harmonic distortion factor. Measurements were conducted on electronic power converters, which are the major sources of harmonic in industrial environment. The results confirmed the high accuracy of estimates. >

The return Raman Lidar signal contains a strong elastically scattered component (at X) that is useful for profiling clouds and aerosols and also weaker inelastically scattered components that provide chemical-specific information. For profiling water vapor, we use components produced by vibrational Raman effect that produces energy shifts characteristic of the molecules in the atmosphere (3652 cm' for water vapor, 233 1 cm1 for nitrogen). The aim of this paper is to process lidar backscattered signal that contains water vapor and aerosol information in order to improve their recovery. Since they are affected by different kinds of noise, an appropriate filtering, with an improved recovery, represents a way to get good estimates of the above components. Water vapor and aerosols are two significant atmospheric components that are generally detected for a better knowledge of weather and climate. In spite of optical filters included in the experimental apparatus used for this paper, there is a need of further filtering, by using signal digital filtering. To discriminate noises from the main signal that is backscattered from sky, we are investigating on the use of appropriate digital filtering to be utilized in order to retrieval a noiseless signal. This approach is different from the current one that uses a poissonian averaging of collected data. In our investigation, we prefer to employ filters that preserve either amplitude information or phase one. Different kinds of filtering procedures have been used in order to isolate the main signal from noise.

The "lidarist" frequently wishes to process his experimental data to obtain as accurate and clean a representation of water vapor as is consistent with his measurement accuracies. In measurements contaminated by high-frequency noise this usually means smoothing the experimental data by some method (which is equivalent to smoothing with a low-pass filter) to eliminate or greatly reduce the amount of high frequency noise without distorting the desired signal. For data which are continuous in time (analog data) this is commonly accomplished using low-pass RC filters. However, with the increasing use of computer-controlled data acquisition systems which record data in digital form, there has developed a need for techniques which perform the same filtering process on the digitized data. Filtering or smoothing process should be as simple and efficient as is consistent with experimental situation. Poissonian averaging has been using for filtering lidar signal data. In previous work we showed the opportunity of using digital filtering in order to overcome problems created by poissonian averaging. To introduce further improvement in filtering we have used binomial filters; some scientists also use differentiating smoothing in an attempt to compensate for the fact that differentiation reduces the signal-to-noise ratio. This can easily be performed with the binomial filter by convolving either the filter coefficients or the data by sequences [1,0, -1]/2. This may be repeated any number of times to obtain the second-third-,and higher-order derivatives, after which the data are low-pass filtered in usual manner. The advantages of the above adjustable windows compared to the fixed windows are their optimality and flexibility. A wavelet analyis is used to increase signal retrieval. Wavelet analysis represents the next logical step: a windowing technique with variable-sized regions. Wavelet analysis allows th use of long time intervals where we want more precise low-frequency information, and shorter regions where we want high-frequency information. Lidar, signal processing, scattering and backscattering, remote sensing, digital filtering, equiripple characteristcs, Kaiser window.