Power Allocation Strategies for Target Localization in Distributed Multiple-Radar Architectures

Godrich, Hana; Petropulu, Athina P.; Poor, H. Vincent

doi:10.1109/tsp.2011.2144976

Cited by 262 publications

(169 citation statements)

References 21 publications

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“…Proof: Optimization problems in the form of (17) have been studied in the OFDM and MIMO literature; e.g., [39] and [40]. The expression in (18) can be derived in a similar fashion to the derivation in [39].…”

Section: ) Optimal Power Allocation Based On Average Crlbmentioning

confidence: 99%

“…First, it is observed that the elements of w defined in the proposition are all positive, which is based on the definitions of a i and r i in (10) and (15), respectively. 6 In addition, from the definition of w, the objective function in (17) can be expressed as w T p J . Then, under the constraints in (17), w T p J can be maximized by assigning the maximum allowed power (i.e., min{P T , P peak h(1) }) to the jammer node corresponding to the largest element of w (that is, the h(1)th element), the remaining power (subject to the peak power constraint) to the jammer node corresponding to the second largest element of w (that is, the h(2)th element), and so on.…”

Section: ) Optimal Power Allocation Based On Average Crlbmentioning

confidence: 99%

“…The problem in [15] is investigated in the presence of collaborative nodes in [16], and the corresponding ranging energy optimization problem and a practical algorithm is proposed. In [17], the optimal power allocation strategies are investigated for target localization in a distributed multiple-radar system, where the total transmit power and the Cramér-Rao lower bound (CRLB) are considered as the two metrics in the optimization problems. Due to non-convexity of the optimization problems, relaxation and domain decomposition methods are employed, which facilitate both central processing at the fusion center and distributed processing.…”

Section: Jamming Of Wireless Localization Systems I Introductionmentioning

confidence: 99%

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Jamming of Wireless Localization Systems

Gezici

Gholami²,

Bayram

et al. 2016

IEEE Trans. Commun.

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Abstract-In this paper, the optimal jamming of wireless localization systems is investigated. Two optimal power allocation schemes are proposed for jammer nodes in the presence of total and peak power constraints. In the first scheme, power is allocated to jammer nodes in order to maximize the average Cramér-Rao lower bound (CRLB) of target nodes, whereas in the second scheme, the power allocation is performed for the aim of maximizing the minimum CRLB of target nodes. Both the schemes are formulated as linear programs, and a closed-form solution is obtained for the first scheme. For the second scheme, under certain conditions, the property of full total power utilization is specified, and a closed-form solution is obtained when the total power is lower than a specific threshold. In addition, it is shown that non-zero power is allocated to at most N T jammer nodes according to the second scheme in the absence of peak power constraints, where N T is the number of target nodes. In the presence of parameter uncertainty, robust versions of the power allocation schemes are proposed. Simulation results are presented to investigate the performance of the proposed schemes and to illustrate the theoretical results.

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Section: ) Optimal Power Allocation Based On Average Crlbmentioning

confidence: 99%

Section: ) Optimal Power Allocation Based On Average Crlbmentioning

confidence: 99%

Section: Jamming Of Wireless Localization Systems I Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Jamming of Wireless Localization Systems

Gezici

Gholami²,

Bayram

et al. 2016

IEEE Trans. Commun.

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show abstract

“…Also, in (12), ϕ ij denotes the angle between target node i and anchor node j. In addition, it is assumed that the elements of a i are non-zero (i.e., strictly positive) for i ∈ {1, 2, .…”

Section: A Crlb For Location Estimation Of Target Nodesmentioning

confidence: 99%

“…Conic programming is employed for efficient solutions, and improvements over uniform power allocation are illustrated. In [12], the optimal power allocation strategies are investigated for target localization in distributed multiple-radar system, where the total transmit power and the CRLB are considered as the two metrics in the optimization problems. In [13], ranging energy optimization is studied for a wireless localization system that performs two-way ranging between a target node and anchor nodes by considering a specific accuracy requirement in a service area.…”

Section: Introductionmentioning

confidence: 99%

Optimal jamming of wireless localization systems

Gezici

Gholami

Bayram

et al. 2015

2015 IEEE International Conference on Communication Workshop (ICCW)

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Abstract-In this study, optimal jamming of wireless localization systems is investigated. Two optimal power allocation schemes are proposed for jammer nodes in the presence of total and peak power constraints. In the first scheme, power is allocated to jammer nodes in order to maximize the average Cramér-Rao lower bound (CRLB) of target nodes whereas in the second scheme the power allocation is performed for the aim of maximizing the minimum CRLB of target nodes. Both schemes are formulated as linear programs, and a closed-form expression is obtained for the first scheme. Also, the full total power utilization property is specified for the second scheme. Simulation results are presented to investigate performance of the proposed schemes.

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Cramér‐Rao Lower Bounds for Joint Target Parameter Estimation in FM‐Based Distributed Passive Radar Network with Antenna Arrays

et al. 2018

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To avoid the disadvantages of the active radar which utilizes its own transmitter to emit electromagnetic radiations, passive radars use the signals readily available in the environment and can provide superior capabilities of stealth target detection, low probability of intercept, low cost, and robustness. This paper investigates the joint target parameter (delay and Doppler) estimation performance for a frequency modulation (FM)‐based distributed passive radar network (DPRN) system with antenna arrays. The DPRN system consists of multiple FM‐based illuminators of opportunity and multiple radar receivers, which are placed on moving platforms. First, we consider the scenario where the target state parameters are unknown, the maximum likelihood estimator is developed, and the log‐likelihood ratio of the received signal for a complex Gaussian extended target is derived. Then, the Cramér‐Rao lower bounds (CRLBs) on the Cartesian coordinates of target position and velocity are computed for a DPRN system with MT FM‐based transmitters of Q antenna elements and MR multichannel receivers of P antenna elements. Finally, numerical examples demonstrate that grouping the receiving antenna elements into properly sized arrays can reduce estimation errors. It is also shown that the joint CRLB is a function of signal‐to‐noise ratio, the number of receiving antenna elements, the properties of the transmitted FM waveform, and the relative geometry between the target and the DPRN architecture. The analytically closed‐form expressions for CRLB are an important performance metric in that they enable the optimal placement of radar receivers to improve the target parameter estimation performance.

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Power Allocation Strategies for Target Localization in Distributed Multiple-Radar Architectures

Cited by 262 publications

References 21 publications

Jamming of Wireless Localization Systems

Jamming of Wireless Localization Systems

Optimal jamming of wireless localization systems

Cramér‐Rao Lower Bounds for Joint Target Parameter Estimation in FM‐Based Distributed Passive Radar Network with Antenna Arrays

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