Remote Sensing Satellite Pointing Error Definition Metric And Budget

With the rapid development of remote sensing technology and the enrichment of types of requirements, there is the increasingly high demand on resolution for remote sensing mission. As the platform of payloads, satellites will be affected by various factors during launch and on-orbit work and service, resulting in pointing errors. Due to the existence of pointing errors, the resolution may be affected, so it is the key factor of high resolution imaging. This paper focuses on the high-resolution remote sensing mission, and carries out a comprehensive research about the definition of point errors, pointing error metrics and pointing error budget, and the main research contents are as follows:Pointing errors are made of the pointing accuracy errors and the pointing stability errors, and the pointing stability errors are made of errors which can lead the smear errors and jitter errors. Low-frequency pointing errors cause mainly the pointing accuracy errors, high-frequency pointing errors causes mainly the pointing stability errors. The time domain and frequency domain metrics for pointing errors is proposed, and the methods of different statistical interpretations for pointing errors and pointing error indices are established. On the basis of this, the pointing errors are modeled by using the state space method. State space model can calculate the pointing error in the analytic form, so it can avoid complex numerical calculations. Referred to point spread function, the effect of pointing errors on the imaging quality is analyzed. Pointing error can widen the point spread function, so it may influence the image quality.The sources which can cause pointing errors are characterized and modeled. During the launch and on-orbit work and service, remote sensing satellite platforms and payloads may be influenced by a lot of error sources, including misalignment, sensors noises, actuator errors and environment disturbance. Pointing error sources are characterized by usage of the probability density functions, and the statistical properties are obtained. The process of the errors transformation is analyzed and modeled. The error contribution methods are proposed, including the pointing errors which are correlated and uncorrelated.The establishment of pointing error budget is analyzed and studied. The steps and process belong to error budget are proposed. Based on the properties of the pointing errors, we can divide the errors into bias, drift error, uniform error, period error, sinusoidal error and random error. By using one example, the error budget is illustrated, and based on the results, we can conclude that in the preliminary design phase or the whole lifetime of the remote sensing project, the pointing error budget plays an important role on it and the research on that is significantly meaningful.