A wideband filtering dielectric patch (DP) antenna with reconfigurable bandwidth is investigated in this paper. Adjusting the aspect ratio of the DP resonator can make the high-order TE ₁₂₁ mode close to the dominate TM ₁₀₁ mode to facilitate the design of wideband filtering DP antenna. Meanwhile, the high-order TM ₁₁₁ mode is adjacent to the TE ₁₂₁ mode and then used as a non-excitation and non-radiation mode for producing an upper band-edge radiation null. On this basis, two slots with different sizes in parallel are introduced into the ground plane to excite the DP resonator, resulting in a lower band-edge radiation null, which sharpens the lower band-edge roll off. A pair of slits between the two coupling slots are incorporated and the varactor diodes are loaded on the slits to tune the electrical distance of the coupling slots, thereby electrically controlling the frequency of the lower band-edge radiation null. In this way, the fractional bandwidth (FBW) of the resultant filtering antenna can be flexibly tuned from 21% to 15.3%. A prototype has been designed, fabricated, and measured. Reasonable agreement was obtained between the simulated and measured results.

In this article, the double-ridge waveguide (WG) is investigated for designing high-performance balanced bandpass filter (BPF) and filtering power divider (FPD). It can be found that the two ridges’ surface currents under fundamental mode operation have inherent characteristic of same amplitude and anti-phase. Based on this, an in-line balanced BPF using double-ridge WG resonators is designed while the coupling between the resonators is fulfilled by the evanescent mode of the rectangular WG. The high common-mode (CM) suppression in the frequency range of interest is obtained naturally. On the basis of the filter prototype, a balanced FPD can be easily implemented by proper adding the outputs on the last ridge resonator. For demonstration, both of them have been fabricated and measured. Measured results indicate that the filtering response centers at 3.5 GHz and the 3-dB fractional bandwidth (FBW) is about 13% with an insertion loss (IL) of $<$ 0.35 dB. Both balanced BPF and FPD have wide and high differential-mode (DM) upper stopband rejection, and the CM suppression is better than 65 dB in the passband.

The key to autonomous navigation in unmanned systems is the ability to recognize static and moving objects in the environment and to support the task of predicting the future state of the environment, avoiding collisions, and planning. However, because the existing 3D LiDAR point-cloud moving object segmentation (MOS) convolutional neural network (CNN) models are very complex and have large computation burden, it is difficult to perform real-time processing on embedded platforms. In this paper, we propose a lightweight MOS network structure based on LiDAR point-cloud sequence range images with only 2.3 M parameters, which is 66% less than the state-of-the-art network. When running on RTX 3090 GPU, the processing time is 35.82 ms per frame and it achieves an intersection-over-union(IoU) score of 51.3% on the SemanticKITTI dataset. In addition, the proposed CNN successfully runs the FPGA platform using an NVDLA-like hardware architecture, and the system achieves efficient and accurate moving-object segmentation of LiDAR point clouds at a speed of 32 fps, meeting the real-time requirements of autonomous vehicles.

A supercompact balanced wideband bandpass filter (BPF) based on capacitor-loaded one-eighth wavelength three-line coupled structure is proposed. Multiple differential-mode (DM) transmission poles, DM transmission zeros, and common-mode (CM) transmission zeros can be obtained and controlled by loading multiple capacitors on the three-line coupled structure, which makes the filter achieve wideband DM filtering response and CM suppression. Compared with the state-of-the-art balanced wideband BPFs, the proposed design has the advantages of compact size and simple structure. A prototype centered at 0.66 GHz with the 3-dB fractional bandwidth of 43.8% is demonstrated, which exhibits the supercompact size of $0.003~\lambda ^{2}_{g}$ ( $\lambda _{g}$ is the guided wavelength at the center frequency) and the minimum insertion loss of 0.43 dB.

This study proposes an uplink reconfigurable intelligent surface (RIS)-aided free-space optical (FSO) and radio frequency (RF) hybrid satellite-terrestrial network (HSTN). We consider the impact of imperfect channel state information (CSI) on the RIS system under fixed-gain amplify-and-forward (AF) and decode-and-forward (DF) relay conditions. We derive closed-form expressions for various performance metrics of the end-to-end signal-to-noise ratio (SNR). We model the FSO link using the Málaga ( $\mathcal {M}$ ) distribution with two detection schemes and use an RIS-aided Rayleigh fading model for the RF link, both of which consider the satellite-terrestrial loss. At high SNRs, we determine the relevant asymptotic expressions and validate the analytical results through Monte Carlo simulations. Additionally, we evaluate the impacts of key system parameters, such as RIS configuration parameters and imperfect CSI, on the end-to-end performance.