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A new X-band retrodirective antenna based on superheterodyne mixer and phase conjugating technology is proposed for inter-satellite data transmission in this paper. The novel phase conjugating circuit, utilizing the reciprocity of the passive mixers, achieves high RF-IF and LO-IF isolations, high communication link gain, and a very compact low profile layout with all antenna elements and circuit components arranged at one common layer of a double-sided printed circuit board (PCB). Its mathematical principles of circuit design are derived, and the effect of up and down conversion loss deviation of mixers on the amplitude and phase error of the circuit, thus on the beam pointing error and the side-lobe of the antenna is discussed. A prototype of circularly polarized one dimension retrodirective antenna is fabricated, and its bistatic RCS measurement in an anechoic chamber is implemented to verify the effectiveness of the proposed antenna array. The results show that, within the scanning range from −30 • to +30 • , the array has good retrodirective performance. The proposed antenna would be a good choice for the inter-satellite data transmission inside a distributed satellite cluster. INDEX TERMS Low profile, phase conjugating, retrodirective antenna, satellite-borne.

The improvement of the spatial and temporal resolution of reflectance data products has been challenging due to the diversity of data sources and availability of many data merging and fusion algorithms. In the algorithmic domain, methods for data merging and fusion may include, but are not limited to, the Modified Quantile-Quantile Adjustment (MQQA), the Bayesian maximum entropy (BME), and the spatial and temporal adaptive reflectance fusion model (STARFM). This paper presents a synergistic integration of the data merging and fusion algorithms of MQQA and BME in dealing with heterogeneous and nonstationary surface reflectance data at both the top of atmosphere (TOA) and land surface for a comparative study. Emphasis has been placed on the distinctive performance between BME and MQQA-BME algorithms in the spatial domain and the MQQA-BME and STARFM in the temporal domain at both TOA and land surface levels. The results indicate that the BME and MQQA-BME outperform the MQQA in terms of the spatial coverage at both TOA and land surface levels. Moreover, the MQQA-BME algorithm shows a higher prediction accuracy than STARFM at the blue band over the temporal domain at both TOA and land surface levels. The results of this comparison will greatly empower the MQQA-BME to be used for urban air quality monitoring and related epidemiological assessment in the future, once finer aerosol optical depth predictions via integrated data merging and fusion can be made possible.