This article describes the design and implementation of a compact CMOS RC frequency reference based on N-type diffusion (N-diff) resistors and metal-insulator-metal (MIM) capacitors. It consists of a frequency-locked loop (FLL) that locks the period of a voltage-controlled oscillator (VCO) to the time it takes a current source to charge a capacitor to a reference voltage. Conventionally, the temperature compensation of such FLLs involves the use of resistors with different temperature dependencies. In this work, however, this is done by using two bipolar junction transistor (BJT)-based current sources with different temperature dependencies to charge a MIM capacitor and generate a reference voltage across an N-diff resistor, respectively. Implemented in a standard 180-nm technology, the resulting frequency reference achieves small size (0.028 mm²), moderate inaccuracy (±900 ppm) from -40 ^°C to 125 ^°C, and low drift (±1600 ppm) after accelerated aging. The versatility of the proposed temperature compensation scheme is validated by replacing the N-diff resistor with a P-poly resistor. However, the latter exhibits greater inaccuracy (+2000/-2500 ppm) and more drift (-2600/-8100 ppm) after accelerated aging.

Satellite observation scheduling plays a significant role in improving the efficiency of Earth observation systems. To solve the large-scale multisatellite observation scheduling problem, this article proposes an ensemble of metaheuristic and exact algorithms based on a divide-And-conquer framework (EHE-DCF), including a task allocation phase and a task scheduling phase. In the task allocation phase, each task is allocated to a proper orbit based on a metaheuristic incorporated with a probabilistic selection and a tabu mechanism derived from ant colony optimization and tabu search, respectively. In the task scheduling phase, we construct a task scheduling model for every single orbit and solve the model by using an exact method (i.e., branch and bound, B&B). The task allocation and task scheduling phases are performed iteratively to obtain a promising solution. To validate the performance of the EHE-DCF, we compare it with B&B, three divide-And-conquer-based metaheuristics, and a state-of-The-Art metaheuristic. Experimental results show that the EHE-DCF can obtain higher scheduling profits and complete more tasks compared with existing algorithms. The EHE-DCF is especially efficient for large-scale satellite observation scheduling problems.