Abstract:k------A tracking algorithm based on a measurement model of the multipath propagation effects on the elevation angle measurements is presented. This algorithm does not depend on the specirk signal processing and the prevailing environmental conditions. The results of simulations based on several scenarios are presented. The signal processing model used to generate the elevation measurements of a low-flying target with multipath effects is also described. This model incorporates a spherical Earth and f i i t e … Show more
“…Fig. 5 shows that when M = 4, the best performance is achieved, which agrees with the analytical results in Section 6 and the conclusion in [21]. Figure 6 depicts the optimal configuration of MIMO radar.…”
Section: Numerical Simulationssupporting
confidence: 84%
“…In [18], the authors investigated the problem of detecting a moving target by exploiting multipath reflections. Other areas of application in which multipath effects are of primary interest are in low-angle tracking [19][20][21].…”
Abstract-In this paper, we focus on target detection and system configuration optimization of Multiple-input Multiple-output (MIMO) radar in low-grazing angle, where the multipath effects are very abundant. The performance of detection can be improved via utilizing the multipath echoes. First, the reflection coefficient, considering the curved earth effect, is derived. Then, the general signal model for MIMO radar is introduced for low-grazing angle. Using the NeymanPearson sense, the detector of MIMO radar with multipath is analyzed. We use the deflection coefficient as a criterion of system configuration both for MIMO radar and phased-array radar. The simulation results show that the performance can be enhanced markedly when the multipath effects are considered, and the optimal configuration of phased-array radar is with the same number of transmitters as that of receivers, however, the optimal configuration of MIMO radar depends on the signal-to-noise ratio (SNR).
“…Fig. 5 shows that when M = 4, the best performance is achieved, which agrees with the analytical results in Section 6 and the conclusion in [21]. Figure 6 depicts the optimal configuration of MIMO radar.…”
Section: Numerical Simulationssupporting
confidence: 84%
“…In [18], the authors investigated the problem of detecting a moving target by exploiting multipath reflections. Other areas of application in which multipath effects are of primary interest are in low-angle tracking [19][20][21].…”
Abstract-In this paper, we focus on target detection and system configuration optimization of Multiple-input Multiple-output (MIMO) radar in low-grazing angle, where the multipath effects are very abundant. The performance of detection can be improved via utilizing the multipath echoes. First, the reflection coefficient, considering the curved earth effect, is derived. Then, the general signal model for MIMO radar is introduced for low-grazing angle. Using the NeymanPearson sense, the detector of MIMO radar with multipath is analyzed. We use the deflection coefficient as a criterion of system configuration both for MIMO radar and phased-array radar. The simulation results show that the performance can be enhanced markedly when the multipath effects are considered, and the optimal configuration of phased-array radar is with the same number of transmitters as that of receivers, however, the optimal configuration of MIMO radar depends on the signal-to-noise ratio (SNR).
“…Moreover, changing the batteries of nodes in some places is difficult, or a (Garnett et al, 2006;Wei et al, 2011). In based techniques, multipath propagation is the typical phenomenon that causes radio signals to Shalom et al, 1994;Saleh and Valenzuela, algorithms can be divided into four major categories, namely, lateration, angulation, shows the categorizations zed by this paper. The second level of this figure presents several algorithms that have been proposed so far.…”
Section: Introductions Of Localization Hardwarementioning
confidence: 98%
“…The ZigBee coordinator carries too many nodes, especially in scale wireless sensor network, which results in inefficient real-time application, data packet loss, and decreased stability. Moreover, changing the batteries of nodes in some places is difficult, or a fairly large number of nodes are troublesome to change (Garnett et al, 2006;Wei et al, 2011) based techniques, multipath propagation is the typical phenomenon that causes radio signals to reach the receiving antenna by two or more paths (Bar-Shalom et al, 1994;Saleh and Valenzuela, Figure 1 Localization hardware Algorithms Review algorithms can be divided into four major categories, namely, lateration, angulation, (Smolau, 2009;Stojmenovic, 2005). Figure 2 shows the categorizations of the localization algorithms organized by this paper.…”
Section: Introductions Of Localization Hardwarementioning
“…The solutions of other variables (such as r 1 , h r ) are omitted for brevity, see [19,21] for more details. The complex reflection coefficient is calculated by [22] ρ = Γ (ν,h) DS (7) where Γ (ν,h) is vertical polarization or horizontal polarization reflection coefficient for a plane surface; D is the divergence factor due to a curved surface; S is root-mean-squared (RMS) specular scattering coefficient which represents the roughness of surface.…”
Abstract-In low grazing angle scenario, target detection performance is seriously deteriorated due to multipath effect. This paper deals with moving target detection in low grazing angle with orthogonal frequency division multiplexing (OFDM) multi-input multi-output (MIMO) radar. We show that the detection performance can be improved through utilizing the multipath effect. Realistic physical and statistical effects such as refraction of the lower atmosphere and the Earth's curvature are incorporated into the multipath propagation model. Then, we derive a generalized likelihood ratio test (GLRT) detector by taking advantage of the frequency diversity of OFDM and MIMO configuration. Based on the fact that the target responses resonate at different frequencies and statistical characteristics of the test, we propose an algorithm which adaptively allocates the transmitted energy to improve the detection performance. The effectiveness of the GLRT detector as well as the adaptive design method is demonstrated via numerical examples.
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