Estimating Living-Body Location Using Bistatic MIMO Radar in Multi-Path Environment

Abstract

This paper proposes a method that uses bistatic Multiple-Input Multiple-Output (MIMO) radar to locate living-bodies. In this method, directions of living-bodies are estimated by the MUltiple SIgnal Classification (MUSIC) method at the transmitter and receiver, where the Fourier transformed virtual Single-Input Multiple-Output (SIMO) channel matrix is used. Body location is taken as the intersection of the two directions. The proposal uses a single frequency and so has a great advantage over conventional methods that need a wide frequency band. Also, this method can be used in multipath-rich environments such as indoors. An experiment is performed in an indoor environment, and the MIMO channels yielded by various subject numbers and positions are measured. The result indicates that the proposed method can estimate multiple living-body locations with high accuracy, even in multipath environments.

Method of Estimating Human Orientation Using Array Antenna

“…To detect the orientation of the subject by using the new antenna arrangement, we propose a new algorithm, which is explained more detailly in the following part of the paper. This is major difference from our previous works [8][9][10]. Figure 1 shows a conceptual diagram of the proposed method.…”

RSSI-Based Living-Body Radar Using Single RF Front-End and Tunable Parasitic Antennas

“…On the other hand, the dotted and dashed lines are the values calculated by simulation. As a first step of the channel estimation, our method assumes a complex channel as shown in (7). The dashed line represents the response calculated by using (8) with the initially assumed channel, and this is indicated as 'Simulated (un optimized).'…”

“…Combining the signals received at all antenna elements yields a high detection rate. The second group aims to find the direction or location of the living-bodies [5], [7]. For detecting the location of a living-body, a key advance was the MIMO radar technique [8].…”

Human Posture Identification Using a MIMO Array

“…To solve this problem, human localization methods suitable for multi-path environments have been proposed. There are three approaches to human localization: time difference of arrival (TDOA) estimation [9,10], object localization [11] based on the multiple signal classification (MUSIC) method [12], and the trigonometry methods based on DOA/DOD estimation using the MUSIC method [13][14][15]. Though the TDOA methods can quickly localize targets even in multi-path environments by using frequency-modulated continuous-wave (FMCW) radar, this method is expensive as it requires a wide bandwidth of 1.79 GHz (from 5.46 to 7.25 GHz).…”

“…Localization based on MUSIC [11] uses a low-frequency band, 250 MHz, and estimates the target location by using spherical-mode MUSIC to process the oscillating return signal. However, the array aperture is comparable to the estimated distance because of the low frequency, and this method requires observation periods of over 10 s. Trigonometry-based localization [13][14][15] uses MIMO radar with DOA estimation by the fast Fourier transform (FFT) technique [16]. However, this method needs to observe the channel for several tens of seconds to accurately capture human activity information.…”