# Design of an Integrated System for Spaceborne SAR Imaging and Data Transmission
###### Abstract
[14] used orthogonal frequency division multiplexing (OFDM) chirp waveforms to embed communication information in the chirp signals. They utilized band-pass filters to eliminate interference signals and successfully implemented MIMO-SAR with OFDM linear frequency modulation waveforms. However, the system was highly complex and required optimization for energy efficiency. Meanwhile, research by [PERSON] et al. [15] focuses on radar applications. They embedded a discrete Fourier transform-based watermarking framework into radar waveforms to enhance security and reduce the probability of signal interception. This enables stable communication and high-quality imaging in multipath and noisy environments. [PERSON] et al. [16] designed a hybrid radar-communication system for estimating statistical channel state information. This system allows for data transmission in low Earth orbit satellite communication and target sensing abilities. [PERSON] et al. [17] and [PERSON] et al. [18] successfully integrated radar and communication functions on spaceborne and ground-based SAR systems using FBMC. Compared to traditional OFDM waveforms, FBMC waveforms offer greater flexibility and higher spectral containment capability, making them a potential modulation waveform for DFRC [18]. Multipath effects arise from echoes originating from different reflecting objects. When the maximum delay of these echoes exceeds the length of the cyclic prefix (CP), inter-symbol interference occurs, disrupting the orthogonality between subcarriers. OQAM modulation shows excellent low sidelobe levels and resistance to multipath in integrated SAR and communication systems. By designing QQAM-OFDM transmission sequences, the need for a cyclic prefix, as in CP-OFDM, is eliminated, thereby enhancing spectral efficiency [19]. Channel estimation (CE) is one of the potential research objects of DFRC. For the radar-centered integration approach, [PERSON] et al. [20] proposed a tensor-decomposition method to estimate multipath channel parameters, including such complex parameters as azimuth and elevation. This method can reconstruct the wireless channel between any pair of transmitting and receiving mobile antennas and use the estimated multipath channel parameters to assist subsequent communication. [PERSON] et al. [21] proposed a method that uses the radar main lobe to estimate the high-moving channels of the perceived targets by utilizing prior knowledge on delays and Doppler frequency shifts at different frequencies. The communication performance of the communication-centric integration approach is generally not affected. When the receiver knows the transmitted waveform a priori, almost all of the communication waveforms can be used for target sensing. [PERSON] et al. [22] implemented channel estimation by using communication waveforms in massive MIMO systems, so as to perceive the information on target parameters and channel states. The framework is suitable for time-varying channels and frequency-selective channels and can be used to solve the squint effect of light beams in space. [PERSON] et al. [23] proposed adopting the multipath OFDM beams received by the passive radar system to estimate the target trajectory as well as the delay Doppler parameters and demodulation errors, so as to enhance the range and velocity resolution in the passive radar system, which would receive the communication and perceive the targets. FBMC modulation signals have a high peak-to-average power ratio (PAPR) because of the extensive overlap of subcarriers. This overlap creates an unstable signal envelope, increasing the PAPR. In low linear amplification regions, this instability can cause significant nonlinear distortions, affecting both in-band and out-of-band signals. As a result, these distortions can degrade the bit error rate (BER) performance of FBMC waveforms and impact target detection capabilities [24]. Controlling the PAPR is essential when designing power allocation strategies.