Design of Frequency Index Modulated Waveforms for Integrated SAR and Communication on High-Altitude Platforms (HAPs)

TL;DR

This paper proposes a novel waveform design combining frequency index modulation and QAM for integrated SAR imaging and communication on high-altitude platforms, enhancing data rate and maintaining resolution.

Contribution

It introduces a frequency index modulation waveform with QAM integration for simultaneous SAR and communication, including ambiguity function analysis and phase compensation algorithms.

Findings

Waveform achieves high data rate with maintained SAR resolution.

Phase compensation improves coherent SAR processing.

Simulations confirm theoretical performance bounds.

Abstract

This paper, addressing the integration requirements of radar imaging and communication for High-Altitude Platform Stations (HAPs) platforms, designs a waveform based on linear frequency modulated (LFM) frequency-hopping signals that combines synthetic aperture radar (SAR) and communication functionalities. Specifically, each pulse of an LFM signal is segmented into multiple parts, forming a sequence of sub-pulses. Each sub-pulse can adopt a different carrier frequency, leading to frequency hops between sub-pulses. This design is termed frequency index modulation (FIM), enabling the embedding of communication information into different carrier frequencies for transmission. To further enhance the data transmission rate at the communication end, this paper incorporates quadrature amplitude modulation (QAM) into waveform design. %For the SAR portion, this approach reduces the ADC sampling requirements while maintaining range resolution. The paper derives the ambiguity function of the proposed waveform and analyzes its Doppler and range resolution, establishing upper and lower bounds for the range resolution. In processing SAR signals, the receiver first removes QAM symbols, and to address phase discontinuities between sub-pulses, a phase compensation algorithm is proposed to achieve coherent processing. For the communication receiver, the user first performs de-chirp processing and then demodulates QAM symbols and FIM index symbols using a two-step maximum likelihood (ML) algorithm. Numerical simulations further confirm the theoretical validity of the proposed approach.