Optimized star sensors laboratory calibration method using a regularization neural network.

High-precision ground calibration is essential to ensure the performance of star sensors. However, the complex distortion and multi-error coupling have brought great difficulties to traditional calibration methods, especially for large field of view (FOV) star sensors. Although increasing the complexity of models is an effective way to improve the calibration accuracy, it significantly increases the demand for calibration data. In order to achieve high-precision calibration of star sensors with large FOV, a novel laboratory calibration method based on a regularization neural network is proposed. A multi-layer structure neural network is designed to represent the mapping of the star vector and the corresponding star point coordinate directly. To ensure the generalization performance of the network, regularization strategies are incorporated into the net structure and the training algorithm. Simulation and experiment results demonstrate that the proposed method can achieve high precision with less calibration data and without any other priori information. Compared with traditional methods, the calibration error of the star sensor decreased by about 30%. The proposed method can satisfy the precision requirement for large FOV star sensors.

An Improved Fast Self-Calibration Method for Hybrid Inertial Navigation System under Stationary Condition.

The navigation accuracy of the inertial navigation system (INS) can be greatly improved when the inertial measurement unit (IMU) is effectively calibrated and compensated, such as gyro drifts and accelerometer biases. To reduce the requirement for turntable precision in the classical calibration method, a continuous dynamic self-calibration method based on a three-axis rotating frame for the hybrid inertial navigation system is presented. First, by selecting a suitable IMU frame, the error models of accelerometers and gyros are established. Then, by taking the navigation errors during rolling as the observations, the overall twenty-one error parameters of hybrid inertial navigation system (HINS) are identified based on the calculation of the intermediate parameter. The actual experiment verifies that the method can identify all error parameters of HINS and this method has equivalent accuracy to the classical calibration on a high-precision turntable. In addition, this method is rapid, simple and feasible.

On-orbit calibration for star sensors without priori information.

The star sensor is a prerequisite navigation device for a spacecraft. The on-orbit calibration is an essential guarantee for its operation performance. However, traditional calibration methods rely on ground information and are invalid without priori information. The uncertain on-orbit parameters will eventually influence the performance of guidance navigation and control system. In this paper, a novel calibration method without priori information for on-orbit star sensors is proposed. Firstly, the simplified back propagation neural network is designed for focal length and main point estimation along with system property evaluation, called coarse calibration. Then the unscented Kalman filter is adopted for the precise calibration of all parameters, including focal length, main point and distortion. The proposed method benefits from self-initialization and no attitude or preinstalled sensor parameter is required. Precise star sensor parameter estimation can be achieved without priori information, which is a significant improvement for on-orbit devices. Simulations and experiments results demonstrate that the calibration is easy for operation with high accuracy and robustness. The proposed method can satisfy the stringent requirement for most star sensors.

Local Observability Analysis of Star Sensor Installation Errors in a SINS/CNS Integration System for Near-Earth Flight Vehicles.

Strapdown inertial navigation system/celestial navigation system (SINS/CNS) integrated navigation is a fully autonomous and high precision method, which has been widely used to improve the hitting accuracy and quick reaction capability of near-Earth flight vehicles. The installation errors between SINS and star sensors have been one of the main factors that restrict the actual accuracy of SINS/CNS. In this paper, an integration algorithm based on the star vector observations is derived considering the star sensor installation error. Then, the star sensor installation error is accurately estimated based on Kalman Filtering (KF). Meanwhile, a local observability analysis is performed on the rank of observability matrix obtained via linearization observation equation, and the observable conditions are presented and validated. The number of star vectors should be greater than or equal to 2, and the times of posture adjustment also should be greater than or equal to 2. Simulations indicate that the star sensor installation error could be readily observable based on the maneuvering condition; moreover, the attitude errors of SINS are less than 7 arc-seconds. This analysis method and conclusion are useful in the ballistic trajectory design of near-Earth flight vehicles.

Angular velocity estimation based on star vector with improved current statistical model Kalman filter.

Angular velocity information is a requisite for a spacecraft guidance, navigation, and control system. In this paper, an approach for angular velocity estimation based merely on star vector measurement with an improved current statistical model Kalman filter is proposed. High-precision angular velocity estimation can be achieved under dynamic conditions. The amount of calculation is also reduced compared to a Kalman filter. Different trajectories are simulated to test this approach, and experiments with real starry sky observation are implemented for further confirmation. The estimation accuracy is proved to be better than 10-4 rad/s under various conditions. Both the simulation and the experiment demonstrate that the described approach is effective and shows an excellent performance under both static and dynamic conditions.

Bilateral inguinal lymphadenectomy using simultaneous double laparoscopies for penile cancer: A retrospective study.

OBJECTIVE: To assess the feasibility, safety, and efficiency of bilateral inguinal lymphadenectomy using simultaneous double laparoscopies for penile cancer. MATERIALS AND METHODS: We reviewed retrospectively the records of 65 patients who underwent inguinal lymph nodes dissection (ILND) for penile cancer from January 2012 to May 2019. Treatments included open ILND (OILND, 19 patients), video-endoscopic inguinal lymphadenectomy (VEIL) using single laparoscopy (S-VEIL, 24 patients), and VEIL using double laparoscopies (D-VEIL, 22 patients). We evaluated the peri-operative and short-term oncological outcomes of the three groups. RESULTS: The mean operative time of D-VEIL (105.91 ± 10.87 minutes) was significantly shorter than the other two groups, OILND shorter than S-VEIL (160.47 ± 13.74 minutes, 191.67 ± 17.80 minutes, respectively) (P < 0.001). Intraoperative blood loss in the S-VEIL and D-VEIL groups were 53.54 ± 8.78 and 48.41 ± 13.22 ml, respectively; they were significantly lower than that of the OILND group (99.74 ± 9.64 ml; P < 0.001). The numbers of unilateral and total lymph nodes harvested were similar in all groups. The complication rates in the S-VEIL group (4.2%) and the D-VEIL group (4.5%) were significantly lower than that in the OILND group (63.2%; P < 0.001). Compared with open surgery (13.53 ± 1.74 days for hospitalization; 11.37 ± 1.92 days for the left side of drain, 11.95 ± 1.84 days for the right side), the two VEIL groups had significantly shorter drainage tube residence time (7.42 ± 2.02 and 7.32 ± 1.52 days, respectively for the left side; 7.63 ± 1.81 and 7.27 ± 1.58 days, respectively for the right side), shorter postoperative hospitalization (9.46 ± 1.64 and 9.00 ± 1.83 days, respectively) (P < 0.001). There were no statistically significant differences in rates of regional recurrence and short-term survival among the three groups. CONCLUSION: Bilateral inguinal lymphadenectomy using double laparoscopies simultaneously can provide adequate oncological outcomes safely and efficiently, and carry significantly lower morbidity than OILND, at a median follow-up of 33.5 months. It is a more time-saving surgical approach for penile cancer patients who need bilateral ILND.

Dopaminergic Projection from Ventral Tegmental Area to Substantia Nigra Pars Reticulata Mediates Chronic Social Defeat Stress-Induced Hypolocomotion.

Numerous human clinical studies have suggested that decreased locomotor activity is a common symptom of major depressive disorder (MDD), as well as other psychiatric diseases. In MDD, the midbrain ventral tegmental area (VTA) dopamine (DA) neurons are closely related to regulate the information processing of reward, motivation, cognition, and aversion. However, the neural circuit mechanism that underlie the relationship between VTA-DA neurons and MDD-related motor impairments, especially hypolocomotion, is still largely unknown. Herein, we investigate how the VTA-DA neurons contribute to the hypolocomotion performance in chronic social defeat stress (CSDS), a mouse model of depression-relevant neurobehavioral states. The results show that CSDS could affect the spontaneous locomotor activity of mice, but not the grip strength and forced locomotor ability. Chemogenetic activation of VTA-DA neurons alleviated CSDS-induced hypolocomotion. Subsequently, quantitative whole-brain mapping revealed decreased projections from VTA-DA neurons to substantia nigra pars reticulata (SNr) after CSDS treatment. Optogenetic activation of dopaminergic projection from VTA to SNr with the stimulation of phasic firing, but not tonic firing, could significantly increase the locomotor activity of mice. Moreover, chemogenetic activation of VTA-SNr dopaminergic circuit in CSDS mice could also rescued the decline of locomotor activity. Taken together, our data suggest that the VTA-SNr dopaminergic projection mediates CSDS-induced hypolocomotion, which provides a theoretical basis and potential therapeutic target for MDD.

Optimal scheme of star observation of missile-borne inertial navigation system/stellar refraction integrated navigation.

To achieve accurate and completely autonomous navigation for spacecraft, inertial/celestial integrated navigation gets increasing attention. In this study, a missile-borne inertial/stellar refraction integrated navigation scheme is proposed. Position Dilution of Precision (PDOP) for stellar refraction is introduced and the corresponding equation is derived. Based on the condition when PDOP reaches the minimum value, an optimized observation scheme is proposed. To verify the feasibility of the proposed scheme, numerical simulation is conducted. The results of the Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) are compared and impact factors of navigation accuracy are studied in the simulation. The simulation results indicated that the proposed observation scheme has an accurate positioning performance, and the results of EKF and UKF are similar.

A Dynamic Precision Evaluation Method for the Star Sensor in the Stellar-Inertial Navigation System.

Integrating the advantages of INS (inertial navigation system) and the star sensor, the stellar-inertial navigation system has been used for a wide variety of applications. The star sensor is a high-precision attitude measurement instrument; therefore, determining how to validate its accuracy is critical in guaranteeing its practical precision. The dynamic precision evaluation of the star sensor is more difficult than a static precision evaluation because of dynamic reference values and other impacts. This paper proposes a dynamic precision verification method of star sensor with the aid of inertial navigation device to realize real-time attitude accuracy measurement. Based on the gold-standard reference generated by the star simulator, the altitude and azimuth angle errors of the star sensor are calculated for evaluation criteria. With the goal of diminishing the impacts of factors such as the sensors' drift and devices, the innovative aspect of this method is to employ static accuracy for comparison. If the dynamic results are as good as the static results, which have accuracy comparable to the single star sensor's precision, the practical precision of the star sensor is sufficiently high to meet the requirements of the system specification. The experiments demonstrate the feasibility and effectiveness of the proposed method.

A hybrid method for accurate star tracking using star sensor and gyros.

Star tracking is the primary operating mode of star sensors. To improve tracking accuracy and efficiency, a hybrid method using a star sensor and gyroscopes is proposed in this study. In this method, the dynamic conditions of an aircraft are determined first by the estimated angular acceleration. Under low dynamic conditions, the star sensor is used to measure the star vector and the vector difference method is adopted to estimate the current angular velocity. Under high dynamic conditions, the angular velocity is obtained by the calibrated gyros. The star position is predicted based on the estimated angular velocity and calibrated gyros using the star vector measurements. The results of the semi-physical experiment show that this hybrid method is accurate and feasible. In contrast with the star vector difference and gyro-assisted methods, the star position prediction result of the hybrid method is verified to be more accurate in two different cases under the given random noise of the star centroid.

False star detection and isolation during star tracking based on improved chi-square tests.

The star sensor is a precise attitude measurement device for a spacecraft. Star tracking is the main and key working mode for a star sensor. However, during star tracking, false stars become an inevitable interference for star sensor applications, which may result in declined measurement accuracy. A false star detection and isolation algorithm in star tracking based on improved chi-square tests is proposed in this paper. Two estimations are established based on a Kalman filter and a priori information, respectively. The false star detection is operated through adopting the global state chi-square test in a Kalman filter. The false star isolation is achieved using a local state chi-square test. Semi-physical experiments under different trajectories with various false stars are designed for verification. Experiment results show that various false stars can be detected and isolated from navigation stars during star tracking, and the attitude measurement accuracy is hardly influenced by false stars. The proposed algorithm is proved to have an excellent performance in terms of speed, stability, and robustness.