scholarly journals ES-DPR: A DOA-Based Method for Passive Localization in Indoor Environments

Sensors ◽  
2019 ◽  
Vol 19 (11) ◽  
pp. 2482 ◽  
Author(s):  
Zhang Chen ◽  
Jinlong Wang
Keyword(s):  
Multipath Propagation ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Recognition Algorithm ◽  
Indoor Environments ◽  
Direct Path ◽  
Multipath Signals ◽  
Localization Approach ◽  
Passive Localization ◽  
Methods Numerical

In this paper, we propose a novel indoor passive localization approach called eigenspace-based DOA with direct-path recognition (ES-DPR), based on a DOA estimation algorithm with multiple omnidirectional antennas deployed in a uniform linear array (ULA). To address the multipath propagation interference problem in the indoor environments, we utilize the azimuth and RSS estimation results, which are calculated by using the eigenspace-based DOA (ES-DOA) algorithm, in a novel style. A direct-path bearing recognition algorithm is introduced to identify the real DOA of the signal source in different indoor environments, by combining the azimuth and RSS estimation with ensemble learning methods. Numerical simulations are conducted to verify the validity and superiority of the proposed method. The results show that the proposed ES-DPR method can achieve high resolution and has strong anti-noise capability in dealing with the multipath signals, and the direct-path recognition algorithm is reliable and robust in different indoor environments, even in undetectable direct-path conditions.

scholarly journals DOA Estimation for Highly Correlated and Coherent Multipath Signals with Ultralow SNRs

2019 ◽  
Vol 2019 ◽  
pp. 1-10
Author(s):  
Li Cheng ◽  
Yang Li ◽  
Lianying Zou ◽  
Yong Qin
Keyword(s):  
Multipath Propagation ◽  
Signal To Noise Ratio ◽  
Main Idea ◽  
Doa Estimation ◽  
Time Shift ◽  
Direct Path ◽  
Multipath Signal ◽  
Highly Correlated ◽  
Multipath Signals ◽  
Cramer Rao Bound

In a typical multipath propagation environment, there exists a strong direct path signal accompanying with several weak multipath signals. Due to the strong direct path interference and other masking effects, the Direction-of-Arrival (DOA) of a weak multipath signal is hard to be estimated. In this paper, a novel method is proposed to estimate the DOA of multipath signals with ultralow signal-to-noise ratio (SNR). The main idea is to increase the SNR and signal-to-interference ratio (SIR) of the desired multipath signal in time-delay domain before DOA estimation processing. Firstly, the cross-correlation functions of the direct path signal and the received array signal are calculated. Then, they are combined and constructed to an enhanced array signal. Under certain conditions, the SNR and SIR of the desired signal can be significantly increased. Finally, the DOAs of multipath signals can be estimated by conventional technologies, and the associated time delays can be measured on the DOA-time-shift map. The SNR and SIR gains of the desired signal are analyzed theoretically, and theoretical analysis also indicates that the Cramer–Rao bound can be reduced. Simulation examples are presented to verify the advantages of the proposed method.

scholarly journals Experimental Evaluation of Multipath Mitigation in TDOA-Based Indoor Passive Localization System Using A Beam Steering Broadband Circular Polarization Antenna

Electronics ◽  
2018 ◽  
Vol 7 (12) ◽  
pp. 362 ◽  
Author(s):  
Changjiang Su ◽  
Yanqun Liu ◽  
Leilei Liu ◽  
Mei Yang ◽  
Hongxin Zhao ◽  
...  
Keyword(s):  
Circular Polarization ◽  
Experimental Evaluation ◽  
Multipath Propagation ◽  
Beam Steering ◽  
Line Of Sight ◽  
Indoor Environments ◽  
Rf Switch ◽  
Multipath Mitigation ◽  
Localization System ◽  
Passive Localization

An experimental evaluation of multipath mitigation using a beam steering broadband circular polarization antenna (BSBCPA) in indoor passive localization system based on time differences of arrival (TDOA) is presented in this paper. The BSBCPA consists of a beam switch network, four identical hexagon patch elements and their respective feeding networks. By controlling the states of a radio frequency (RF) switch in the beam switch network, four steering circular polarization beams can be excited separately for azimuth omnidirectional coverage. Combining the spatial selectivity of steering beams and circular polarization in the BSBCPA, the positioning inaccuracy from indoor multipath propagation can be mitigated. In two different indoor environments with line of sight (LOS), complex multipath, when transmitting a 20 MHz bandwidth signal in WLAN, the 2D positioning mean error obtained is 0.7 m and 0.82 m, respectively. Compared with conventional omnidirectional linear polarization antenna (OLPA), the BSBCPA can at least improve positioning accuracy by 51%. The experimental results show that the proposed BSBCPA can significantly mitigate multipath propagation for TDOA-based indoor passive localization.

scholarly journals An Enhanced Smoothed L0-Norm Direction of Arrival Estimation Method Using Covariance Matrix

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4403
Author(s):  
Ji Woong Paik ◽  
Joon-Ho Lee ◽  
Wooyoung Hong
Keyword(s):  
Covariance Matrix ◽  
Phased Array ◽  
Null Space ◽  
Estimation Method ◽  
Direction Of Arrival ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Direction Of Arrival Estimation ◽  
Improve Performance ◽  
Space Projection

An enhanced smoothed l0-norm algorithm for the passive phased array system, which uses the covariance matrix of the received signal, is proposed in this paper. The SL0 (smoothed l0-norm) algorithm is a fast compressive-sensing-based DOA (direction-of-arrival) estimation algorithm that uses a single snapshot from the received signal. In the conventional SL0 algorithm, there are limitations in the resolution and the DOA estimation performance, since a single sample is used. If multiple snapshots are used, the conventional SL0 algorithm can improve performance in terms of the DOA estimation. In this paper, a covariance-fitting-based SL0 algorithm is proposed to further reduce the number of optimization variables when using multiple snapshots of the received signal. A cost function and a new null-space projection term of the sparse recovery for the proposed scheme are presented. In order to verify the performance of the proposed algorithm, we present the simulation results and the experimental results based on the measured data.

scholarly journals A Direction-of-Arrival Estimation Algorithm Based on Compressed Sensing and Density-Based Spatial Clustering and Its Application in Signal Processing of MEMS Vector Hydrophone

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2191
Author(s):  
Huichao Yan ◽  
Ting Chen ◽  
Peng Wang ◽  
Linmei Zhang ◽  
Rong Cheng ◽  
...  
Keyword(s):  
Compressed Sensing ◽  
Spatial Clustering ◽  
Direction Of Arrival ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Cluster Center ◽  
Direction Of Arrival Estimation ◽  
Vector Hydrophone ◽  
Regularization Parameters ◽  
Selection Of

Direction of arrival (DOA) estimation has always been a hot topic for researchers. The complex and changeable environment makes it very challenging to estimate the DOA in a small snapshot and strong noise environment. The direction-of-arrival estimation method based on compressed sensing (CS) is a new method proposed in recent years. It has received widespread attention because it can realize the direction-of-arrival estimation under small snapshots. However, this method will cause serious distortion in a strong noise environment. To solve this problem, this paper proposes a DOA estimation algorithm based on the principle of CS and density-based spatial clustering (DBSCAN). First of all, in order to make the estimation accuracy higher, this paper selects a signal reconstruction strategy based on the basis pursuit de-noising (BPDN). In response to the challenge of the selection of regularization parameters in this strategy, the power spectrum entropy is proposed to characterize the noise intensity of the signal, so as to provide reasonable suggestions for the selection of regularization parameters; Then, this paper finds out that the DOA estimation based on the principle of CS will get a denser estimation near the real angle under the condition of small snapshots through analysis, so it is proposed to use a DBSCAN method to process the above data to obtain the final DOA estimate; Finally, calculate the cluster center value of each cluster, the number of clusters is the number of signal sources, and the cluster center value is the final DOA estimate. The proposed method is applied to the simulation experiment and the micro electro mechanical system (MEMS) vector hydrophone lake test experiment, and they are proved that the proposed method can obtain good results of DOA estimation under the conditions of small snapshots and low signal-to-noise ratio (SNR).

Multi-frame DOA Estimation Algorithm for Weak Moving Targets

2020 ◽  
Author(s):  
Penghui Zhang ◽  
Kezhu Liu ◽  
Wujun Li ◽  
Wei Yi ◽  
Xiaobo Yang
Keyword(s):  
Estimation Algorithm ◽  
Doa Estimation ◽  
Moving Targets
Sign in / Sign up

Export Citation Format

Share Document