LEO-Based Satellite Constellation for Moving Target Detection

With the rapid development of cooperative detection technology, target fusion detection with regard of LEO satellites can be realized by means of their diverse observation configurations. However, the existing constant false alarm ratio (CFAR) detection research rarely involves the space-based target fusion detection theory. In this paper, a novel multi-source fusion detection method based on LEO satellites is presented. Firstly, the pre-compensation function is constructed by employing the range and Doppler history of the cell where the antenna beam center is pointed. As a result, not only is the Doppler band broadening problem caused by the high-speed movement of the satellite platform, but the Doppler frequency rate (DFR) offset issue resulted from different observation configurations are alleviated synchronously. Then, the theoretical upper and lower limits of DFR are designed to achieve the effective clutter suppression and the accurate target echo fusion. Finally, the CFAR detection threshold based on the exponential weighted likelihood ratio is derived, which effectively increases the contrast ratio between the target cell and other background cells, and thus to provide an effective multi-source fusion detection method for LEO-based satellite constellation. Simulation results verify the effectiveness of the proposed algorithm.

Jitter Detection Method Based on Sequence CMOS Images Captured by Rolling Shutter Mode for High-Resolution Remote Sensing Satellite

Satellite platform jitter is a non-negligible factor that affects the image quality of optical cameras. Considering the limitations of traditional platform jitter detection methods that are based on attitude sensors and remote sensing images, this paper proposed a jitter detection method using sequence CMOS images captured by rolling shutter for high-resolution remote sensing satellite. Through the three main steps of dense matching, relative jitter error analysis, and absolute jitter error modeling using sequence CMOS images, the periodic jitter error on the imaging focal plane of the spaceborne camera was able to be measured accurately. The experiments using three datasets with different jitter frequencies simulated from real remote sensing data were conducted. The experimental results showed that the jitter detection method using sequence CMOS images proposed in this paper can accurately recover the frequency, amplitude, and initial phase information of satellite jitter at 100 Hz, 10 Hz, and 2 Hz. Additionally, the detection accuracy reached 0.02 pixels, which can provide a reliable data basis for remote sensing image jitter error compensation.

Fusion Retrieval of Sea Surface Barometric Pressure from the Microwave Humidity and Temperature Sounder and Microwave Temperature Sounder-II Onboard the Fengyun-3 Satellite

Both the Microwave Humidity and Temperature Sounder (MWHTS) and the Microwave Temperature Sounder-II (MWTS-II) operate on the Fengyun-3 (FY-3) satellite platform, which provides an opportunity to retrieve the sea surface barometric pressure (SSP) with high accuracy by fusing the observations from the 60 GHz, 118.75 GHz, and 183.31 GHz channels. The theory of retrieving SSP using passive microwave observations is analyzed, and the sensitivity test experiments of MWHTS and MWTS-II to SSP as well as the test experiments of the contributions of MWHTS and MWTS-II to SSP retrieval are carried out. The theoretical channel combination is established based on the theoretical analysis, and the SSP retrieval experiment is carried out based on the Deep Neural Network (DNN) for the theoretical channel combination. The experimental results show that the retrieval accuracy of SSP using the theoretical channel combination is higher than that of MWHTS or MWTS-II. In addition, based on the test results of the contributions of MWHTS and MWTS-II to the retrieval SSP, the optimal theoretical channel combination can be built, and can further improve the retrieval accuracy of SSP from the theoretical channel combination.

Fixed-time sliding mode attitude control of a flexible spacecraft with rotating appendages connected by magnetic bearing

<abstract> <p>This study focuses on the attitude control of a flexible spacecraft comprising rotating appendages, magnetic bearings, and a satellite platform capable of carrying flexible solar panels. The kinematic and dynamic models of the spacecraft were established using Lagrange methods to describe the translation and rotation of the spacecraft system and its connected components. A simplified model of the dynamics of a five-degrees-of-freedom (DOF) active magnetic bearing was developed using the equivalent stiffness and damping methods based on the magnetic gap variations in the magnetic bearing. Next, a fixed-time sliding mode control method was proposed for each component of the spacecraft to adjust the magnetic gap of the active magnetic bearing, realize a stable rotation of the flexible solar panels, obtain a high inertia for the appendage of the spacecraft, and accurately control the attitude. Finally, the numerical simulation results of the proposed fixed-time control method were compared with those of the proportional-derivative control method to demonstrate the superiority and effectiveness of the proposed control law.</p> </abstract>

High-Precision Angle Prediction of Sun for Space Remote Sensing Instrument

In order to grasp the timing of sun calibration in advance, this paper introduces a high-precision method to predict the solar angle by using the current broadcast time and orbital instantaneous root of the satellite platform. By calculating the sun’s apparent right ascension and apparent declination, the conversion matrix from the geocentric inertial coordinate system to the orbital coordinate system, and the satellite attitude correction matrix, the sun vector in the satellite body coordinate system is obtained. This method is used to predict the sun angle of a sun synchronous orbit in the satellite coordinate system, and the prediction results are compared with the STK simulation results. The results show that the sun angle prediction error of this method is less than ±0.003°. It can meet the requirements of on-orbit solar calibration. The main error sources in the prediction method are analysed.

Fifty years of balloon-borne ozone profile measurements at Uccle, Belgium: a short history, the scientific relevance, and the achievements in understanding the vertical ozone distribution

Starting in 1969 and comprising three launches a week, the Uccle (Brussels, Belgium) ozonesonde dataset is one of longest and densest in the world. Moreover, as the only major change was the switch from Brewer-Mast (BM) to electrochemical concentration cell (ECC) ozonesonde types in 1997 (when the emissions of ozone-depleting substances peaked), the Uccle time series is very homogenous. In this paper, we briefly describe the efforts that were undertaken during the first 3 decades of the 50 years of ozonesonde observations to guarantee the homogeneity between ascent and descent profiles, under changing environmental conditions (e.g. SO2), and between the different ozonesonde types. This paper focuses on the 50-year-long Uccle ozonesonde dataset and aims to demonstrate its past, present, and future relevance to ozone research in two application areas: (i) the assessment of the temporal evolution of ozone from the surface to the (middle) stratosphere, and (ii) as the backbone for validation and stability analysis of both stratospheric and tropospheric satellite ozone retrievals. Using the Long-term Ozone Trends and Uncertainties in the Stratosphere (LOTUS) multiple linear regression model (SPARC/IO3C/GAW, 2019), we found that the stratospheric ozone concentrations at Uccle have declined at a significant rate of around 2 % per decade since 1969, which is also rather consistent over the different stratospheric levels. This overall decrease can mainly be assigned to the 1969–1996 period with a rather consistent rate of decrease of around −4 % per decade. Since 2000, a recovery of between +1 % per decade and +3 % per decade of the stratospheric ozone levels above Uccle has been observed, although it is not significant and is not seen for the upper stratospheric levels measured by ozonesondes. Throughout the entire free troposphere, a very consistent increase in the ozone concentrations of 2 % per decade to 3 % per decade has been measured since both 1969 and 1995, with the trend since 1995 being in almost perfect agreement with the trends derived from the In-service Aircraft for a Global Observing System (IAGOS) ascent/descent profiles at Frankfurt. As the number of tropopause folding events in the Uccle time series has increased significantly over time, increased stratosphere-to-troposphere transport of recovering stratospheric ozone might partly explain these increasing tropospheric ozone concentrations, despite the levelling-off of (tropospheric) ozone precursor emissions and notwithstanding the continued increase in mean surface ozone concentrations. Furthermore, we illustrate the crucial role of ozonesonde measurements for the validation of satellite ozone profile retrievals. With the operational validation of the Global Ozone Monitoring Experiment-2 (GOME-2), we show how the Uccle dataset can be used to evaluate the performance of a degradation correction for the MetOp-A/GOME-2 UV (ultraviolet) sensors. In another example, we illustrate that the Microwave Limb Sounder (MLS) overpass ozone profiles in the stratosphere agree within ±5 % with the Uccle ozone profiles between 10 and 70 hPa. Another instrument on the same Aura satellite platform, the Tropospheric Emission Spectrometer (TES), is generally positively biased with respect to the Uccle ozonesondes in the troposphere by up to ∼ 10 ppbv, corresponding to relative differences of up to ∼ 15 %. Using the Uccle ozonesonde time series as a reference, we also demonstrate that the temporal stability of those last two satellite retrievals is excellent.

A Design of a Developable Automatic Avoidance System of UAV Based on ADS-B

There are two primary defects in the existing UAV avoidance systems: the system is memoryless; airborne radars are used to detect long-distance barriers, which are unreliable and expensive. The paper adopts the deep learning algorithm and ADS-B communication system based on a satellite base station to solve the above problems. It divides the avoidance problem into two parts: short-distance obstacle avoidance and long-distance route planning. On the one hand, the system establishes the knowledge base storing the previous avoidance experience and the matching mechanism, realizing the correspondence between input and experience through a deep learning algorithm. They can dramatically improve the reaction speed and safety of UAVs. On the other hand, the system realizes the interconnection between UAV and the satellite base station through the ADS-B communication system to replace the radars, putting the task of route planning on the satellite platform. Therefore, the satellite can achieve large-scale and all-weather detection to improve the overall safety of UAVs depending on its high and long-range characteristics. The paper also illustrates the design elements of the RF baseband integrated ADS-B transceiver and the simulation performance of the short-distance avoidance system in the end, whose results show that the system can be applied to dense obstacle environments and significantly improve the security of UAVs in a complex domain.