References of "Shankar, Bhavani"
     in
Bookmark and Share    
Full Text
Peer Reviewed
See detailDistributed 5G NR-based integrated sensing and communication systems: Frame structure and performance analysis
Shi, Shengnan; Cheng, Ziyang; Wu, Linlong UL et al

in 2022 30th European Signal Processing Conference (EUSIPCO) (2022, October 18)

This paper discusses a distributed Integrated Sensing and Communication (ISAC) network based on 5G NR. Each BS in the cellular network adopts half-duplex operation, and every three adjacent BSs construct ... [more ▼]

This paper discusses a distributed Integrated Sensing and Communication (ISAC) network based on 5G NR. Each BS in the cellular network adopts half-duplex operation, and every three adjacent BSs construct a cooperative sensing system. Based on the 5G NR standard frame configuration, we develop a new procedure and protocol to support the proposed ISAC network. Under this network, we analyze the performance of both sensing and communication in practical scenarios. Simulations show the effectiveness of the proposed ISAC network. [less ▲]

Detailed reference viewed: 29 (1 UL)
Full Text
Peer Reviewed
See detailRKHS Based State Estimator for Radar Sensor in Indoor Application
Kumar Singh, Uday UL; Shankar, Bhavani; Alaee, Mohammad

Scientific Conference (2022, April 23)

For the estimation of targets’ states (location, velocity, and acceleration) from nonlinear radar measurements, usually, the improved version of well known Kalman filter: extended Kalman filter (EKF) and ... [more ▼]

For the estimation of targets’ states (location, velocity, and acceleration) from nonlinear radar measurements, usually, the improved version of well known Kalman filter: extended Kalman filter (EKF) and unscented Kalman filter (UKF) are used. However, EKF and UKF approximates the nonlinear measurement function either by Jacobian or using sigma points. Consequently, because of the approximation of the measurement function, the EKF and UKF cannot achieve high estimation accuracy. The potential solution is to replace the approximation of nonlinear measurement function with its estimate, obtained in high dimensional reproducing kernel Hilbert space (RKHS). An ample amount of research has been done in this direction, and the combined filter is termed RKHS based Kalman filter. However, there is a shortage of literature dealing with estimating the dynamic state of the target in an indoor environment using RKHS based Kalman filter. Therefore, in this paper, we propose the use of RKHS based Kalman filter for indoor application. Specifically, we validate the suitability of the RKHS based Kalman filtering approach using simulations performed over three different target motion models. [less ▲]

Detailed reference viewed: 63 (7 UL)
Full Text
Peer Reviewed
See detailOne-bit ADCs/DACs based MIMO radar: Performance analysis and joint design
Deng, Minglong; Cheng, Ziyang; Wu, Linlong UL et al

in IEEE Transactions on Signal Processing (2022), 70

Extremely low-resolution (e.g. one-bit) analog-to-digital converters (ADCs) and digital-to-analog converters (DACs) can substantially reduce hardware cost and power consumption for MIMO radar especially ... [more ▼]

Extremely low-resolution (e.g. one-bit) analog-to-digital converters (ADCs) and digital-to-analog converters (DACs) can substantially reduce hardware cost and power consumption for MIMO radar especially with large scale antennas. In this paper, we focus on the detection performance analysis and joint design for the MIMO radar with one-bit ADCs and DACs. Specifically, under the assumption of low signal-to-noise ratio (SNR) and interference-to-noise ratio (INR), we derive the expressions of probability of detection ( Pd ) and probability of false alarm ( Pf ) for one-bit MIMO radar and also the theoretical performance gap to infinite-bit MIMO radars for the noise-only case. We further find that for a fixed Pf , Pd depends on the defined quantized signal-to-interference-plus-noise ratio (QSINR), which is a function of the transmit waveform and receive filter. Thus, an optimization problem arises naturally to maximize the QSINR by joint designing the waveform and filter. For the formulated problem, we propose an alternating waveform and filter design for QSINR maximization (GREET). At each iteration of GREET, the optimal receive filter is updated via the minimum variance distortionless response (MVDR) method, and due to the difficulty in global optimality, an alternating direction method of multipliers (ADMM) based algorithm is devised to efficiently find a high-quality suboptimal one-bit waveform. Numerical simulations are consistent to the theoretical performance analysis and demonstrate the effectiveness of the proposed design algorithm. [less ▲]

Detailed reference viewed: 28 (1 UL)
Full Text
Peer Reviewed
See detailMeeting the Lower Bound on Designing Set of Unimodular Sequences with Small Aperiodic/Periodic ISL
Alaee-Kerahroodi, Mohammad UL; Shankar, Bhavani; Mishra, Kumar Vijay et al

in 2019 20th International Radar Symposium (IRS) (2019)

Detailed reference viewed: 104 (2 UL)