Zhonghe Jin’s research while affiliated with Zhejiang University and other places

At present, satellite constellations are a hot topic in the field of aerospace research. Due to the low cost and short design cycle, the micro-satellite is very suitable for constellation. Time synchronization is important for autonomous positioning, navigation, and collaborative work in constellation systems. Current methods for achieving time synchronization in satellite constellations typically involve utilizing timing services from GNSS and ground stations, as well as equipping satellites with atomic clocks exhibiting high-frequency stability. Additionally, some methods require that all satellites are in mutual visibility to enable accurate time difference measurements. However, these approaches do not meet the requirements of autonomy, miniaturization, and large scale. In light of the aforementioned issues, this paper puts an autonomous constellation time synchronization method that measures and compensates for time differences through inter-satellite links. Based a virtual large-scale constellation, experimental simulation results show that the constellation time is synchronized hourly basis in 24 h, it can maintain a maximum time difference of constellation below 1us.

This paper presents a high-performance MEMS accelerometer with ultralow noise and wide bandwidth based on a force control of a mechanical system with high quality-factor (Q factor) and quasi-zero effective stiffness. Both dynamic model and noise model of the proposed accelerometer were developed. Based on the dynamic model, a new damping controller and a phase compensation controller are proposed to improve the bandwidth for the high Q factor accelerometers. The noise model is verified experimentally, indicating that the readout circuit noise and mechanical thermal noise are greatly reduced by the decrease of the effective stiffness and air damping, respectively. The accelerometer with phase compensation controller exhibits a linear relationship between the noise power and the bandwidth, which can be tuned by adjusting the controller parameters. Finally, the bandwidth of ranging from 130 to 381 Hz and the base noise of ranging from 140 ng √Hz⁻¹ to 860 ng √Hz⁻¹ are achieved for the proposed accelerometer.

To address the inadequacies of traditional Advanced Orbiting Systems (AOS) multiplexing algorithms in accommodating the networked and diverse transmission demands of space data, this paper proposes an efficient network AOS integrated multiplexing algorithm based on elastic time slots. The AOS network traffic is categorized into three types based on its characteristics, and a strongly scalable AOS integrated multiplexing model is established, which consists of a packet multiplexing layer, a virtual channel multiplexing layer, and a decision-making layer. For synchronous services, an isochronous frame generation algorithm and a periodic polling virtual channel scheduling algorithm are employed to meet the periodic transmission requirements. For asynchronous non-real-time services, a high-efficiency frame generation algorithm and a uniform queue length virtual channel scheduling algorithm are utilized to satisfy the high-efficiency transmission requirements. For asynchronous real-time services, an adaptive frame generation algorithm based on traffic prediction and a virtual channel scheduling algorithm based on comprehensive channel state are proposed. These algorithms optimize frame generation efficiency and dynamically calculate optimal scheduling results based on virtual channel scheduling status, transmission frame scheduling status, virtual channel priority status, and traffic prediction status, thereby meeting the high dynamics, low latency, and high efficiency transmission requirements. Additionally, a slot preemption-based elastic time slot scheduling strategy is proposed at the decision layer, which dynamically adjusts and optimizes the time slot allocation for the three types of traffic based on the current service request status and time slot occupancy status. Simulation results show that the proposed algorithm not only achieves lower average delay, fewer frame residuals, and higher transmission efficiency, but also maintains high stability under different working conditions, effectively meeting the transmission requirements of various types of space network traffic.

The performance of conventional detection algorithms in small aircraft target detection is often unsatisfactory due to the intricate backgrounds of remote sensing images and the diminutive size of aircraft targets. Furthermore, prevalent deep learning algorithms typically prove overly complex for integration into resource-constrained satellite platforms. In response to these challenges, an enhanced algorithm named LEN-YOLO (Lite backbone - Enhanced Neck - YOLO) has been devised to enhance detection accuracy while preserving model simplicity for the detection of small aircraft in satellite on-orbit scenarios. First, the EIoU Loss is adopted for target localization, enabling the network to effectively focus on small aircraft targets. Second, a Lite backbone is designed by discarding high semantic information, using low-semantic feature maps to detect small targets. Finally, a Bidirectional Weighted FPN based on SimAM and GSConv (BSG-FPN) is proposed to fuse feature maps of different scales to increase detailed information. Experimental results on RSOD and DIOR datasets demonstrate compared to the baseline YOLOv5, LEN-YOLO achieves an increase of 5.1% and 4.2% in $\text {AP}_s$ respectively. Notably, parameters are reduced by 78.3% and floating-point operations by 33.2%.

Low-performing GPS receivers, often used in challenging scenarios such as attitude maneuver and attitude rotation, are frequently encountered for micro–nano satellites. To address these challenges, this paper proposes a modified robust adaptive hierarchical filtering algorithm (named IARKF). This algorithm leverages robust adaptive filtering to dynamically adjust the distribution of innovation vectors and employs a fading memory weighted method to estimate measurement noise in real time, thereby enhancing the filter’s adaptability to dynamic environments. A segmented adaptive filtering strategy is introduced, allowing for flexible parameter adjustment in different dynamic scenarios. A micro–nano satellite equipped with a miniaturized dual-frequency GPS receiver is employed to demonstrate precise orbit determination capabilities. On-orbit GPS data from the satellite, collected in two specific scenarios—slow rotation and Earth-pointing stabilization—are analyzed to evaluate the proposed algorithm’s ability to cope with weak GPS signals and satellite attitude instability as well as to assess the achievable orbit determination accuracy. The results show that, compared to traditional Extended Kalman Filters (EKF) and other improved filtering algorithms, the IARKF performs better in reducing post-fit residuals and improving orbit prediction accuracy, demonstrating its superior robustness. The three-axes orbit determination internal consistency precision can reach the millimeter level. This work explores a feasible approach for achieving high-performance orbit determination in micro–nano satellites.

This paper focuses on automatic temperature sensitivity calibration and nonlinearity optimization of the scale factor (SF) for micro-electromechanical system gyroscopes under force rebalanced operation. The calibration of the SF temperature sensitivity is done based on stiffness modulation by injecting a cosine calibration signal to modulate the resonance frequency of the gyroscope drive mode. The parameters affecting the gyroscope SF are reciprocally proportional to the loop gain of the demodulated calibration signal, enabling a calibrated temperature insensitive SF. Implementing this real-time SF calibration algorithm in an field-programmable gate array (FPGA) platform results in a decreased SF error from 42 416 ppm to 12 141 ppm over a temperature range of 0 °C–50 °C, which is further reduced to 3526 ppm by calibrating the temperature coefficient of the gain ratio of drive and sense mode front-end excitation circuits with the experiment. Additionally, we reveal that the force misalignment angle is a major error source of SF nonlinearity, which is verified experimentally with the result that the SF residual error within the range of 0.1 deg s⁻¹–200 deg s⁻¹ decreases from 8550 ppm to 3963 ppm by force misalignment angle compensation with force rotation matrices. Due to the elimination of parameters affecting both the SF calibration loop and the real angular readout loop and further calibration of the gain ratio temperature sensitivity of discrete boards, the SF error over temperature is reduced by 12 times, while the maximum SF residual error is optimized by two times as a result of the force misalignment angle compensation.

In recent years, the low Earth orbit microsatellite network technology has experienced rapid development due to its advantages of low latency, low cost, and short development cycles. However, building an efficient and reliable satellite network routing system faces many challenges due to the characteristics of satellite networks, such as fast-changing topology, large variations in link latency, higher probabilities of node and link failures, and limited resources. Routing algorithms have a significant impact on intersatellite communication and have become a research hotspot. The current mainstream algorithms focus on reducing information propagation delays between satellites to enable faster transmission. However, many satellite networks, such as meteorological observation satellite networks, are not sensitive to propagation delays but emphasize reducing hardware costs, especially for the receiving and transmitting signal systems of satellites. This means minimizing the single-step signal transmission distance of satellites. This article proposes a routing algorithm based on time slot planning and the shortest path step length. Experimental simulation results demonstrate that this algorithm significantly reduces the step length of signal transmission and lowers hardware costs.