OTFS-based ISAC for active channel sensing and low-altitude multi-target detection

The integrated sensing and communication(ISAC) system based on orthogonal time frequency space(OTFS) as the transmission waveform is recognized for its higher efficiency of resources, making it one of the key technologies for addressing the shortage of spectrum resources. As the number of sensing targets increases, the difference in signal power received by the base station from the superposition of multiple sensing echo signals becomes less significant. Traditional multi-target channel sensing and target detection algorithms result in error transmission and accumulation, thereby degrading the performance of the system's channel sensing and target detection. A maximum likelihood estimator based multi-objective channel parameter sensing and target detection algorithm was proposed to improve the estimation accuracy of the sensed channel and target parameters. Specifically, the parallel interference cancellation(PIC) algorithm was adopted to the received superimposed signals. The signals were reconstructed using the results obtained from the previous iteration and were subtracted from the received signals. The signal-to-interference-plus-noise ratio of the echo signals in the estimation of the sensed channel and target parameters was improved, so the performance of the maximum likelihood estimator was improved. Simulation results show that the proposed algorithm outperforms the traditional ones in terms of channel estimation accuracy. Additionally, the convergence of the proposed algorithm is also validated to be overhead saving.