In this study, we analyze index modulation (IM) based on circularly-shifted chirps (CSCs) for dual-function radar & communication (DFRC) systems. We develop a maximum likelihood (ML) range estimator that considers multiple scatters. To improve the correlation properties of the transmitted waveform and estimation accuracy, we propose index separation (IS) which separates the CSCs apart in time. We theoretically show that the separation can be large under certain conditions without losing the spectral efficiency (SE). Our numerical results show that the IS combined ML and linear minimum mean square error (LMMSE)-based estimators can provide approximately 3 dB signal-to-noise ratio (SNR) gain in some cases while improving estimation accuracy substantially without causing any bit-error ratio (BER) degradation at the communication receiver.
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