Matlab codes will be available soon!
- M. Alaee-Kerahroodi, M. Modarres-Hashemi and M. M. Naghsh, “Designing Sets of Binary Sequences for MIMO Radar Systems,” in IEEE Transactions on Signal Processing, vol. 67, no. 13, pp. 3347-3360, 1 July1, 2019.
- M. Alaee-Kerahroodi, M. Modarres-Hashemi, M. M. Naghsh, B. Shankar and B. Ottersten, “Binary Sequences Set with Small ISL for MIMO Radar Systems,” 2018 26th European Signal Processing Conference (EUSIPCO), Rome, 2018, pp. 2395-2399.
- M. Alaee-Kerahroodi, M. R. Bhavani Shankar, K. V. Mishra and B. Ottersten, “Meeting the Lower Bound on Designing Set of Unimodular Sequences with Small Aperiodic/Periodic ISL,” 2019 20th International Radar Symposium (IRS), Ulm, Germany, 2019, pp. 1-13.
How to design sets of orthogonal sequences?
In Multiple Input Multiple Output (MIMO) radar systems, the complexity of waveform design problem increases with the number of transmit sequences. Indeed, auto- and crosscorrelation functions of the transmitted set of sequences play an important role in discriminating them at the receive side using appropriate matched filters. In this respect, several approaches including frequency-division-multiplexing (FDM), Doppler-division multiplexing (DDM), time-division-multiplexing (TDM) and code-division-multiplexing (CDM) have been developed in the literature.
In CDM-MIMO radar systems, the requirement is to design set of sequences with smallest possible auto- and cross-correlation sidelobes, to be able to separate the transmitted sequences from any other members of the set at any time shift.
Designing Sets of Binary Sequences for MIMO Radar Systems
In this paper, we aim at designing sets of binary sequences with good aperiodic/periodic auto- and cross-correlation functions for multiple-input multiple-output (MIMO) radar systems. We show that such a set of sequences can be obtained by minimizing a weighted sum of peak sidelobe level (PSL) and integrated sidelobe level (ISL) with the binary element constraint at the design stage. The sets of designed sequences are neighboring the lower bound on ISL and have a better PSL than the best-known structured sets of binary sequences. To formulate the problem, we introduce a Pareto-objective of weighted auto- and cross-correlation functions by establishing a multi-objective NP-hard constrained optimization problem. Then, by using the block coordinate descent framework, we propose an efficient monotonic algorithm based on fast Fourier transform, to minimize the multi-dimensional objective function. Numerical results illustrate the superior performance of the proposed algorithm in comparison with the state-of-the-art methods.
Will be completed soon!