The channelized technology can be used in an IF (Intermediate Frequency) module which is a crucial component in a hyperspectral microwave radiometer. In this article, an effective method with which we can eliminate the effect of the transition band of a lowpass filter by designing a WOLA (Weighted Overlap-add) filter bank is put forward. The main idea of this method is to avoid spectrum aliasing at or near the boundary frequencies by constraining the parameters of a WOLA filter bank. To verify this method, we design a practical WOLA filter bank to measure the PSDs (Power Spectral Density) of a multitone signal and a broadband signal compared with a DFT (Discrete Fourier Transform) filter bank. The test results show the specific WOLA filter bank can measure the PSD of an input signal correctly even though the frequency components of input are located in or near the boundary frequencies. The specific WOLA filter bank can be used in an IF module in a hyperspectral microwave radiometer.

For hyperspectral microwave radiometer, its intermediate frequency (IF) module need to divide the signal into thousands of channels. The ADC output of the IF module will up to dozens of GSPS. In order to process such huge data in real time, the FPGA of IF module needs to spend a lot of resources and energy to process the data in parallel, which limited the development of hyperspectral microwave radiometer. In this paper, a method to reduce the FPGA resource consumption for IF module of hyperspectral microwave radiometer is proposed. Using the relationship between odd and even sequences of real signals and complex FFT core, the utilization rate of FPGA resources is improved and the resource consumption of IF module is reduced effectively. The theories, resource consumption analyze, and test results are shown in this paper, which verified that this method can be applied to the optimize the IF Module of hyperspectral microwave radiometer very well.

In this article, the system design of the IF (Intermediate Frequency) module which is a crucial component of hyperspectral microwave radiometers is introduced. The IF module consists of 6.4GSPS sampling-rate ADC (Analog-To-Digital Convert) and Virtex-7 FPGA (Field Programmable Gate Array). The module is a real-time system with a frequency bandwidth of 3.2GHz and a spectral resolution of 6.25MHz. The 1024-point FFT (Fast Fourier Transform) algorithm which takes 160ns to accomplish an entire calculation is implemented in an FPGA. The effective number of channels of this module is 512 because of the symmetry conjugate of the FFT output. The test results of this module are given and analyzed, including the system response of deterministic signals and stochastic signals. The linearity of this module is also measured with the correlation coefficient which is up to 0.9999. The IF module can be widely used in hyperspectral microwave radiometers in various applications.

In this paper, an IF (intermediate frequency) module for hyperspectral microwave radiometers is introduced. The IF module is designed with two 6.4 GSPS sampling-rate ADCs and a Virtex-7 FPGA. The module can achieve 512 channels output for each ADC and process all the sampled data in realtime. The test results of this module are given and analyzed, such as linearity, sensitivity.

In this work, an IF(intermediate frequency) module of a hyperspectral microwave radiometer based on a polyphase filter bank (PFB) and Discrete Fourier Transformation (DFT)is introduced. The IF module is designed with an 800MSPS sampling-rate ADC and a Xilinx Virtex-7 FPGA. The module can achieve 512 channels and a bandwidth of 400M and process all the sampled data in real-time. The test results of this module are given and analyzed, such as linearity, accuracy, etc. It can be used in various applications of microwave remote sensing. The system has strong expandability.

As requirements for the spatial and temporal resolution of remote sensing images for Earth observations increase, the image data has exploded. However, a large amount of remote sensing image data requires a huge channel capacity for transmission. In order to improve the transmission efficiency, the images need to be compressed before transmission. Traditional fractal coding compression technology can greatly reduce the size of image files, but its blocking effect will blur the important texture information of remote sensing images. In addition, the extremely long fratal compression time makes it unsuitable for image transmission. To solve these problems, we propose a fast fractal coding method based on wavelet transform. This method can not only greatly increase the fractal coding speed, but also make the compressed image clear enough to retain texture information.

In this study, the back propagation neural network (BPNN) is applied to retrieve atmospheric temperature profiles, using 50~70 GHz passive microwave brightness temperature values. This paper makes a comparison of the retrieval of atmospheric temperature using the statistical inversion method and the BPNN inversion method. The results of the retrieval experiment show that the accuracy of the BPNN is better than that of the statistical inversion method in the upper atmosphere. It is of great application value to study the retrieve of atmospheric temperature profiles.

Leaf area index (LAI) is very important for crop growth monitoring, biomass estimation, and many plant growth simulation models. Direct methods are the most accurate, but they have the disadvantage of being extremely time-consuming and labor-intensive as a consequence making them not be the preferred solutions. Indirect methods mainly include the radiometric method, inclined point quadrats, and hemispherical canopy photography. This paper focuses on the analysis of the principles and characteristics of the three indirect methods and affirms the advantages and development value of hemispheric canopy photography. The probability model is used to verify the feasibility of LAI inversion which is based on hemispheric canopy photography. In this paper, the canopy images of four sample plots on the campus were collected for LAI estimation, and the results were compared with LAI-2200C. Finally, the improvement of hemispherical canopy photography has prospected.

Humidity is a critical parameter for microwave remote sensing. The method of the microwave resonator to measure humidity is fast, accurate, and real-time. In this paper, a microwave humidity sensor based on the substrate integrated waveguide resonator is designed. The sensor uses a hollow FR-4 substrate structure, which reduces the loss of FR-4 substrate at high frequency and improves the sensitivity of the sensor. The design has a simple structure, low cost, and simplifies the process of the humidity sensor based on thermodynamics and optics. Simulation and experiment results show that the sensor can measure the humidity well.

Soil moisture is a critical parameter for microwave remote sensing. In this paper, a probe based on a microstrip resonance ring (MRR) is designed. The fitting curve between resonant frequency, Q-factor, and complex dielectric constant are obtained by electromagnetic simulation. To measure the moisture of soil, a density-independent factor is introduced to remove the effect of density of soil, which makes this sensor more accurate and easy to use, especially suitable for fieldwork. The experimental results show that this sensor works very well in measuring moisture and complex dielectric constant of soil.

In this work, an IF (intermediate frequency) module of a hyperspectral microwave radiometer is introduced. The IF module is designed with a 5GSPS sampling-rate ADC and a Virtex-7 FPGA. The module can achieve 512 channels and process all the sampled data in real-time. The test results of this module are given and analyzed, such as linearity, sensitivity, etc. It can be used in various applications of microwave remote sensing.

The hyperspectral microwave radiometer has a large number of channels, which results in the decrease of the measuring signal sensitivity. We propose two optimizations based on the design of the hyperspectral microwave radiometer, one is the increase of word length of the system; the other is the improvement of the window function. These optimizations not only effectively reduce the noise level of the system, but also have certain suppression effects on the signal spectrum leakage. Firstly, this article introduces the advantages of the hyperspectral microwave radiometer in the field of microwave remote sensing. Secondly, the structure of the IF module digital circuit of the microwave radiometer is established. Finally, some deficiencies in this system are obtained through theoretical derivation. The radiometer intermediate frequency module is optimized to improve the measurement sensitivity of the hyperspectral microwave radiometer.

With the continuous development of optical lens and imaging chip technology, the fisheye camera method has been widely studied in the world because of its characteristics of TRAC instrument and LAI-2200C coronal analyzer. To obtain the critical ecological parameter of the leaf area index at low cost, a synchronous LAI-2200C leaf area index hemispheric image acquisition system was proposed in this paper. The system consists of an embedded platform, a low-cost image sensor, and a fisheye lens, fixed to the LAI-2200C optical sensor detector, triggered by the LAI-2200C synchronous of hemispheric vegetation image. This study used the system to measure the coronary photos of the tall shrubs in the Chengdu area at different times. It used an image processing algorithm to analyze and obtain LAI. The results show that there is a significant linear correlation between LAI and LAI-2200C measurements obtained by the Fisheye Camera Method (DH-P) (R2= 0.814), the average square root error is 0.278.The test results show that the system can effectively collect the image of the vegetation canopy can be low-cost, and obtain a leaf area index results with minor error.

Leaf area index (LAI) is the basic factor to understand canopy productivity, soil water evaporation, total transpiration loss, and soil temperature. On the basis of analyzing the merits and demerits of various LAI measurement methods, this paper affirms the development prospect and application value of the hemispherical image method. The paper focuses on the inversion theory of LAI and the extraction of canopy porosity. The essence of the hemispherical image method is further elaborated: after the canopy porosity is obtained by image processing, LAI is retrieved based on Lambert-Beer law. In this paper, four tall arbor forests of Chengdu city are selected as research objects to explore the method of obtaining LAI by hemispherical images and compare with LAI-2200C Plant Canopy Analyzer. The results show that LAI measurement based on the hemispherical image is feasible and credible.