Flexible ku/k band frequency reconfigurable bandpass filter

<abstract> <p>The proposed reconfigurable BPF satisfies the International Telecommunication Unionos (ITU) region 3 spectrum requirement. In transmit mode, the frequency range 11.41-12.92 GHz is used by the direct broadcast service (DBS) and the fixed satellite service (FSS). Direct broadcast service (DBS) in reception mode employs 11.7-12.2 GHz and 17.3-17.8 GHz frequency ranges. Frequency reconfigurable filters are popular because they can cover wide range of frequencies, reducing system cost and space. Another emerging trend is electronic component flexibility or conformability, which allows them to be mounted on non-planar objects and are used in wearable applications. This project contains a frequency-reconfigurable BPF that has been entirely printed on a flexible polimide substrate. Frequency reconfigurability is obtained by using a pin diode HSCH 5318 and it is used to switch between 12 GHz and 18 GHz. The prototype reconfigurable BPF is highly compact and low-cost due to the flexible polimide substrate and the measured results are promising and match the simulated results well.</p> </abstract>

Hierarchical Classification Method for Radio Frequency Interference Recognition and Characterization in Satcom

The Quality of Service (QoS) and security of Satellite Communication (Satcom) are crucial as Satcom plays a significant role in a wide range of applications, such as direct broadcast satellite, earth observation, navigation, and government/military systems. Therefore, it is necessary to ensure that transmissions are incorruptible, particularly in the presence of challenges such as Radio Frequency Interference (RFI), which is of primary concern for the efficiency of communications. The security of a wireless communication system can be improved using a robust RFI detection method, which could, in turn, lead to an effective mitigation process. This paper presents a new method to recognize received signal characteristics using a hierarchical classification in a multi-layer perceptron (MLP) neural network. The considered characteristics are signal modulation and the type of RFI. In the experiments, a real-time video stream transmitted in the direct broadcast satellite is utilized with four modulation types, namely, QPSK, 8APSK, 16APSK, and 32APSK. Moreover, it is assumed that the communication signal can be combined with one of the three significant types of interference, namely, Continuous Wave Interference (CWI), Multiple CWI (MCWI), and Chirp Interference (CI). In addition, two robust feature selection techniques have been developed to select more informative features, which leads to improving the classification precision. Furthermore, the robustness of the trained techniques is assessed to predict unknown signals at different Signal to Noise Ratios (SNRs).

The Impact of Low Latency Satellite Sounder Observations on Local Severe Storm Forecasts in Regional NWP

The forecasts of local severe storms (LSS) are highly dependent on how well the pre-convection environment is characterized in the numerical weather prediction (NWP) model analysis. The usefulness of the forecasts is highly dependent on how frequently the forecast is updated. Therefore, the data latency is critical for assimilation into regional NWP models for it to be able to assimilate more data within the data cut-off window. These low latency data can be obtained through direct broadcast sites and direct receiving systems. Observing system experiments (OSE) were performed to study the impact of data latency on the LSS forecasts. The experiments assimilated all existing observations including conventional data (from the global telecommunication system, GTS) and satellite sounder radiance data (AMSU-A (The Advanced Microwave Sounding Unit-A), ATMS (Advanced Technology Microwave Sounder), CrIS (Cross-track Infrared Sounder), and IASI (Infrared Atmospheric Sounding Interferometer)). They were carried out in a nested domain with a horizontal resolution of 9 km and 3 km in the weather research and forecasting (WRF) model. The forecast quality scores of the LSS precipitation forecasts were calculated and compared with different data cut-off widows to evaluate the impact of data latency. The results showed that low latency can lead to an improved and positive impact on precipitation and other forecasts, which indicates the potential application of LEO direct broadcast (DB) data in a high-resolution regional NWP for LSS forecasts.