ترجمه مقاله نقش ضروری ارتباطات 6G با چشم انداز صنعت 4.0
- مبلغ: ۸۶,۰۰۰ تومان
ترجمه مقاله پایداری توسعه شهری، تعدیل ساختار صنعتی و کارایی کاربری زمین
- مبلغ: ۹۱,۰۰۰ تومان
Abstract
In this paper, a sparsity-aware hybrid target localization method in multiple-input-multiple-output (MIMO) radars from time difference of arrival (TDOA) and angle of arrival (AOA) measurements is proposed. This method provides a maximum likelihood estimate of target position by employing compressive sensing techniques. A blockwise approach is addressed in order to achieve better accuracy for a constant computational complexity. The mismatch problem due to grid discretization is also tackled by a dictionary learning technique. The Cramer–Rao lower bound for this model is derived as a benchmark. Numerical simulations are included to corroborate the theoretical developments.
5. Conclusion
In this paper, we formulated the problem of target localization in MIMO radars in sparse representation framework.The proposed method solves the sparsity-aware ML estimation of target’s position by utilizing TDOA and AOA measurements and employs an iterative blockwise technique to reduce complexity and enhance accuracy, simultaneously. Then we proposed a dictionary learning based method to mitigate the off-grid mismatch due to discretization. The effectiveness of the proposed method was verified by simulation results.