Cramer-Rao Bounds of Localization Estimation for Integrated Radar and Communication System

Abstract

Instead of only considering the radar estimation error in the traditional radar system (TRS), for the integrated radar and communication system (IRCS), we investigate the Cramer-Rao bound (CRB) of the localization estimation, which is influenced by both radar estimation error and communication transmission error. The functions of radar and communication are operated simultaneously by embedding the communication symbols into the multicarrier radar waveforms. Firstly, we derive the CRB of time/direction of arrival (TOA/DOA) estimation. To minimize the estimation error, we maximize the signal-to-interferenceplus-noise ratio (SINR) of radar by iteratively optimizing the radar transmit and receive beamformers (with the constraint of available transmit power). Then, the CRB of localization estimation is derived using hybrid TOA/DOA measurement. The local CRBs from different IRCSs are fused according to the linear fusion rule at the fusion center (FC). Finally, numerical results demonstrate that the additional estimation errors for the IRCS are mainly determined by the channel conditions of communication and available transmit power; the estimation accuracy for both IRCS and TRS can be improved through the iterative transmit and receive beamforming (ITRB) technique. INDEX TERMS Cramer-Rao bound, localization estimation, multicarrier waveform, beamforming, integrated radar and communication system.

Performance Analysis of Data Transmission for Joint Radar and Communication Systems

“…Recent information battlefield scenarios urge modern radar equipment to deploy optimally [1,2] and exchange the estimation information [3] with each other. How to form an integrated system by combining the radar equipment with the communication equipment and solve the problems of the generalization, such as tremendous wireless data traffic, rational use of the system resources [4][5][6] has been the theme of increasing research over recent years.…”

Determination of CRLB and Minimum Variance Unbiased Estimator of a DC Signal in AWGN Using Laplace Transform

“…This lower bound can easily help select the best estimator for a given problem in hand based on the minimum variance it can attain. On the other language, the bound tells how best one can achieve during a given estimation problem (Alslaimy and Smith, 2019;Huang et al, 2020;Hung et al, 2020;Kay, 1993;Khorasani et al, 2020;Li et al, 2021;Mao et al, 2020;Tian et al, 2020).…”

“…In radar applications in which the CRLB depends on the geometry of the bistatic configuration, it is normally used to determine the optimal transceiver locations so that the estimation accuracy is improved (Alslaimy and Smith, 2019). Among its features, CRLB can readily give a Minimum Variance Unbiased Estimator (MVUE), if it exist (Alslaimy and Smith, 2019;Kay, 1993;Tian et al, 2020) .…”

“…Furthermore, a strong knowledge of probability and statistics is necessary as well to help evaluate the expected value. It is true, with no doubt, that probability is marked by many scholars as among the difficult branches in mathematics (Kay, 1993;Tian et al, 2020). In short, even though the CRLB is preferred compared to other lower bounds existing in literatures, but its procedure is not straightforward for the reasons outlined earlier (Kay, 1993;Khorasaniet al, 2020;Maoet al, 2020).…”

Determination of Cramer-Rao Lower Bound (CRLB) and Minimum Variance Unbiased Estimator of a DC Signal in AWGN Using Laplace Transform

“…This lower bound can easily help select the best estimator for a given problem in hand based on the minimum variance it can attain. On the other language, the bound tells how best one can achieve during a given estimation problem (Alslaimy and Smith 2019, Huang et al 2020, Hung et al 2020, Kay 1993, Khorasani et al 2020, Li et al 2021, Mao et al 2020, Tian et al 2020.…”