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The objectives of a satellite mission are accomplished by the hardware (i.e., instruments) and software, which are referred to as payloads, aboard the satellite platform. Payloads sense or interact with the subject, are typically unique to each mission, and are the fundamental reason that the satellite is flown. The purpose of the rest of the satellite subsystems is to keep the payload functional and pointed in the right direction. The payload largely determines the mission’s cost, complexity, and effectiveness. A critical part of mission analysis and design is to understand what drives a particular set of payloads so that these demands can become part of the overall system-trade process designed to meet mission objectives at minimal cost and risk.
The key performance parameters of Earth-observation satellites include SNR, spatial resolution, spectral resolution, ground swath, etc. Satellite data users often require and/or prefer receiving satellite images with higher-performance parameters, for instance, a higher SNR and spatial resolution (i.e., finer ground footprint size), in order to obtain accurate information and better serve their applications. Designing and building a satellite with considerably higher-performance parameters is costly. It is also challenging due to the limited availability of technology, which could significantly increase the risk of the mission.
Innovative technologies have been developed and reported that have enhanced the performance parameters of satellites using signal processing approaches by exploiting the intrinsic characteristics of the payloads, as shown in Fig. 10.1. These technologies demonstrate that it is feasible and more cost-effective to enhance satellite performance using signal processing approaches.
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