Algebraic solution for three‐dimensional TDOA/AOA localisation in multiple‐input–multiple‐output passive radar

An efficient estimator for source localization using TD and AOA measurements in MIMO radar systems

“…In this part, we exhibit the performance of the proposed method and compare it with the methods [12]- [13]. Meanwhile, the CRLB is also considered as a benchmark in the RMSE comparison.…”

“…Localization methods [6][7][8][9][10][11][12][13] in MIMO systems can be attributed to use different measurements, including time delay (TD), bistatic range (BR), angle of arrival (AOA), and their combinations. The doppler shift (DS) and bistatic range rate (BRR) can be also utilized when the source and/or receivers are moving [14][15][16][17].…”

“…Reference [13] firstly established pseudo-linear equation with nuisance parameters, the second step refined the final solution by estimating the error of the first step to improve the estimated accuracy. Both the two methods can achieve Cramér-Rao lower bound (CRLB) a low noise level.…”

“…However, the performance degradation occurs to the method [12] at a high noise level due to the presence of measurement noises in both the regressor and regressand. Similarly, the squaring operations of the Second stage in [13] may also lead to increased bias as well as poor positioning accuracy when the noise is large.…”

“…In this letter, we propose an explicit solution based on TD and AOA measurements for target localization in MIMO radar systems. To the best of our knowledge, the expectation value of the cost function is not considered in the WLS solution [12] and [13]. To better handle the randomness of the regressor and regressand introduced by noise in the WLS solution, the proposed method aims to minimize the cost function by imposing a quadratic constraint such that the expectation of the cost function will attain its minimum value in the case of the true solution.…”