In the guidance and control of the first-stage recovery of rocket, the carrier pose measurement is very important. Inertial navigation, satellite navigation, LiDAR are usually used to measure the pose in engineering, while there is no precedent for visual measurement. Visual measurement has the advantages of no cumulative error and high update rate, and has the potential to be applied to rocket recovery. In this paper, the dynamics model of rocket recovery is analyzed and trajectory simulation is carried out, and the Falcon9 rocket is taken as the simulation object and the optimal trajectory is obtained by a convex optimization method. Four cameras were installed in the first stage of the rocket, and the visual pose measurement was realized through the multi-vision sensor measurement model, image target recognition and feature picking. The calculation results show that the visual measurement technology proposed in this paper has a high position accuracy and has the prospect of engineering application.

To systematically evaluate the accuracy of GPS LNAV and CNAV broadcast ephemerides and verify their performance in real-time applications, this study conducted a year-long accuracy assessment for 2024 based on GNSS broadcast and precise ephemerides, complemented by validation through real-time orbit determination (RTOD) experiments using LEO satellites. Broadcast and precise ephemerides from 2024 were used to perform statistical analyses of ephemeris accuracy across different satellite blocks and navigation message types. In addition, reduced-dynamic RTOD experiments were carried out using onboard GPS observations from the GRACE-FO C satellite to assess the impact of different broadcast ephemerides on orbit accuracy. The results show that the accuracy of broadcast ephemerides varies significantly among satellite blocks, with BLOCK IIIA performing the best and BLOCK IIF performing the worst. After the clock source switch on G08 and G10 in 2024, the constellation-averaged SISRE for LNAV and CNAV broadcast ephemerides reached 25.5 cm and 23.8 cm, respectively, representing a substantial improvement compared to the LNAV SISRE of 37.0 cm in 2021. The LEO RTOD experiments further demonstrated that, compared to LNAV, CNAV provides improved accuracy in the along-track, cross-track, radial, and 3D directions, with a maximum reduction in 3D orbit error of 0.8 cm and an average improvement of about 3.2%, thereby confirming the advantage of CNAV in real-time applications. Overall, both the ephemeris accuracy statistics and LEO RTOD results consistently indicate that CNAV broadcast ephemerides outperform LNAV. With the gradual retirement of BLOCK IIR satellites and the continued deployment of BLOCK IIIA satellites, navigation, positioning, and timing services based on CNAV broadcast ephemerides are expected to achieve even higher accuracy, further enhancing their value for real-time positioning and scientific applications.

Given the vulnerability of satellite signals to interference, the research on anti-jamming algorithms based on array antennas becomes crucial to ensure the reliable positioning accuracy of GNSS receivers. However, the existing variable step-size power inversion algorithms rely on the single regulation mechanism of instantaneous energy, which have insufficient stability in the dynamic interference scenarios. This paper proposes a variable step-size anti-jamming algorithm modified by power change rate, and this method adds the power change rate to correct the step-size variation based on the original variable step-size. Through the dual adjustment mechanism of input power normalization and output power change rate correction, the proposed algorithm is promoted to restore quickly the stable convergence state after an abrupt power change. This method effectively mitigates the violent oscillation of the weights caused by rapid power changes, improving both the convergence speed and robustness of the algorithm in the dynamic interference environment. Simulation experiments show that the proposed algorithm achieves faster convergence speed and deeper null depths than a single adjustment mechanism relying solely on instantaneous energy. Moreover, it can effectively cope with the impact of abrupt changes in signal power on interference suppression, thereby reducing interference signal power.

With the rapid development of satellite communication technology, the volume of data transmitted between satellites and ground stations continues to increase, driving higher demands for signal transmission rates and quality. In traditional modulators, due to limitations such as DAC(Digital-to-Analog Converter)sampling rates and shaping filter technologies, low-order modulation is often adopted, resulting in lower signal transmission rates that cannot meet the requirements of future high-speed transmission. Therefore, a 16-channel parallel shaping filter technology with a continuously variable transmission rate is proposed in this paper. This technology employs 64APSK(Amplitude Phase Shift Keying)modulation to achieve high-speed data transmission. Experimental results show that, based on the existing hardware platform, data transmission at a rate of 7.2 Gbps is achieved with a 4.8 GHz DAC sampling rate, and the EVM (Error Vector Magnitude)is as low as 2.029 9%. Compared to the original high-speed modulator architecture, this technology offers advantages such as high transmission rates, good signal quality, and low resource consumption, making it a valuable reference for the design of future systems for data transmission exceeding 10 Gbps.

To counteract the influence of the Earth's non-spherical perturbation, Geostationary Earth Orbit (GEO) satellites must periodically execute longitude drift control to maintain their position in the east-west direction. East-west station-keeping is typically achieved via pulse ignition. During this process for geostationary orbit satellites, continuous telecommand must be sent, severely restricting payload applications closely coupled with satellite telecommand. This paper devises a decentralized control approach for the east-west station-keeping of GEO satellites, constructs a mathematical model, formulates control strategies and implementation details, and validates the control effectiveness using two distinct types of in-orbit satellites. This method efficiently exploits fragmented resources during payload task intervals, enhancing the availability of satellite tracking, telemetry, and telecontrol command resources.

In autonomous driving within the Internet of Vehicles (IoV), positioning accuracy is key to stable operation. However, standalone navigation systems such as satellite navigation and inertial navigation cannot fully ensure continuous high-precision positioning. Therefore, achieving high-precision positioning through information collaboration between vehicles has become the main approach. This paper proposes a neural network-based large-scale cooperative vehicle positioning method. Aiming at the characteristic of vehicles freely gathering and dispersing during driving, principal component analysis is introduced to process navigation information and reduce computational complexity. Furthermore, the Fireworks Neural Network method is used to rapidly fuse navigation information in the IoV, ensuring positioning accuracy and stability during vehicle operation. Compared with existing cooperative positioning methods, experimental results show that the proposed method has faster convergence and better positioning stability.

With the development of measurement and control technology, the Ka-band has become an important direction for the development of next-generation satellite communications and millimeter-wave radar. Low-noise amplifiers are core components at the front end of receivers, and their noise temperature directly affects key system indicators such as the receiving sensitivity and action distance of the system. This paper introduces an ultra-low-noise temperature amplifier working in the Ka-band, achieving ultra-wideband, ultra-low noise temperature, miniaturization and generalization. The measured results show that within the frequency range of 26.5～40 GHz, the gain is more than 35 dB, the noise temperature is less than 215 K, and the VSWR is less than 2.38 with the size of 32 mm×19 mm×8 mm.

Integrated circuit nanotechnology is gradually approaching the physical limit. Therefore, relying on heterogeneous integration technology to continue and expand Moore Law is becoming increasingly important. The vertical interconnection of signals from various integrated chips is achieved through technologies such as through silicon via (TSV) or through glass via (TGV), while high-density interconnection in the horizontal direction can be achieved through rewiring layer (RDL) technology. The article summarizes the comparison between TGV technology and adapter boards, elaborates on the current application status in the field of passive systems and RF 3D integration, analyzes the TGV process capability and the current technical progress of domestic and foreign manufacturers, and explores the existing technical difficulties and future development trends of the TGV.

The objective of coverage path planning is to ensure that Unmanned Aerial Vehicles (UAVs) achieve complete coverage of the target area. Previous studies assigned UAVs the task of covering each sub-area separately. However, this study proposes a new methodology in which two UAVs collaborate across the entire search area, achieving coverage tasks more flexibly while enhancing efficiency. This paper aims to address the high cost of traditional UAV coverage path planning by proposing a dual-UAVcoverage path planning algorithm based on Q-Learning. To reduce the time taken for the process, a grid-based rotating area partitioning algorithm is used to minimize the search area. The path planning is transformed into a multi-objective function optimisation problem, and the Double-Q-Learning algorithm balances global search and local exploitation, iteratively optimising the path with a total cost function that considers distance and turning costs. The simulation results demonstrate that the proposed algorithm can achieve complete coverage of different target areas with a lower total cost.

Digital channelization has been widely applied in the field of electronic reconnaissance. The multi-phase structure of digital channelization can reduce data rates, making it easier to implement in FPGA. However, when the number of sub-channels is large, the data rate of each sub-channel will be significantly lower than the processing rate of FPGA, resulting in a waste of FPGA resources. In this paper, we introduce two-dimensional DFT into traditional DFT digital channelization structure and propose a channelization structure that matches the processing rate of FPGA, namely the digital channelization structure based on two-dimensional DFT. This structure is verified through simulation in Matlab(Matrix Laboratory)，and its computational complexity is analyzed and compared with that of traditional DFT-based digital channelization structure. Subsequently, the FPGA implementation block diagram and FPGA resource utilization are presented, and then the structure is tested on a hardware platform. The results show that the digital channelization structure based on two-dimensional DFT can correctly perform channelization of various signals. Compared with the traditional DFT-based digital channelization structure, it reduces computational complexity and significantly improves the efficiency of FPGA resources utilization, facilitating the FPGA implementation of large-scale digital channelization, which has certain engineering significance.