A Modified Zadoff-Chu Sequence Approach for Sidelobe Suppression and Signal Detection Enhancement in Software-Defined Platforms

In radar and communication systems, Zadoff-Chu (ZC) sequences are used due to their properties, such as its constant modulus and good correlation properties. However, it exhibits non-negligible sidelobes in its autocorrelation function due to factors of finite precision arithmetic and the discrete nature of digital signals, especially if implemented using software-defined systems. The presence of sidelobes poses a significant challenge, as it can degrade signal detection performance and increase the likelihood of false alarm targets in radar systems. To address this issue, this paper aims to modify the existing ZC sequence by relaxing the relative prime number between the root index and ZC length and introducing a novel approaches to mitigate sidelobe effects and enhance the utility of these sequences in practical applications. Furthermore, the proposed method improves radar detection capabilities, particularly in multi-target scenarios. The method is also compatible with MIMO radar systems without the need for orthogonal codes at the receiver end. In addition, this approach offers improved Doppler resilience as the intra-pulse correlation reduces the impact of the Doppler effect on the entire pulse. We demonstrate the effectiveness of our proposed technique through simulations and analysis, demonstrating its potential impact on software-defined radar and communication systems in applications requiring high resolution and accurate target detection.