Joint Antenna Placement and Power Allocation for Target Detection in a Distributed MIMO Radar Network

Qi, Cheng; Xie, Junwei; Zhang, Haowei

doi:10.3390/rs14112650

Cited by 7 publications

(3 citation statements)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…are selected and reconstructed to achieve the given task. Due to the multiple targets tracking is related to the data-level and information-level fusion, more scholars pay attention to optimising multi-target tracking performance through radar resource management in the traditional netted radar systems [11][12][13][14][15][16][17]. For instance, Zhang et al [11] propose a dynamic antenna selection strategy to improve the worst case of estimate accuracy among multi-target tracking.…”

Section: Introductionmentioning

confidence: 99%

Resource allocation scheme of netted radar system for target localisation

Guo

Tao

2023

IET Radar Sonar & Navi

View full text Add to dashboard Cite

In order to enhance the resource utilisation of the netted radar system, a receiving resource allocation (RRA) strategy for target localisation is developed in this article. Receiving resource refers to the receiving node and the processing approach adopted. The aim of the proposed RAA strategy is to select the receiver node and corresponding processing approach to minimise the resource cost while satisfying the desired target localisation accuracies. The resource cost includes the implementation cost of the processing approaches and the distance cost of data transmission. The Cramer‐Rao bound (CRB) incorporating the above controllable parameters is derived and used as the target localisation performance metric in the netted radar system. Whereafter, the RRA problem is modelled as a non‐convex constrained optimisation problem with the discrete variables. A scheme based on the modified depth‐first search is proposed to solve this problem. Simulation results demonstrate that the proposed scheme can effectively reduce resource consumption under the desired target localisation performance constraints.

show abstract

Section: Introductionmentioning

confidence: 99%

Resource allocation scheme of netted radar system for target localisation

Guo

Tao

2023

IET Radar Sonar & Navi

View full text Add to dashboard Cite

show abstract

“…The distributed fusion schemes use covariance intersection fusion. [15] Designs a joint antenna placement and power allocation technique in MIMO radar with widely separated antennas to increase target detection performance. First, a problem for the Neyman-Pearson detector by using the Lagrange power allocation scheme and the antenna deployment optimization is considered.…”

Section: -Introductionmentioning

confidence: 99%

A New Power Allocation Optimization for One Target Tracking in Widely Separated MIMO Radar

Akhondi Darzikolaei,

Karami-Mollaei,

Najimi

2023

jist

View full text Add to dashboard Cite

In this paper, a new power allocation scheme for one target tracking in MIMO radar with widely dispersed antennas is designed. This kind of radar applies multiple antennas which are deployed widely dispersed from each other. Therefore, a target is observed simultaneously from different uncorrelated angles and it offers spatial diversity. In this radar, a target's radar cross section (RCS) is different in each transmit-receive path. So, a random complex Gaussian RCS is supposed for one target. Power allocation is used to allocate the optimum power to each transmit antenna and avoid illuminating the extra power in the environment and hiding it from interception. This manuscript aims to minimize the target tracking error with constraints on total transmit power and the power of each transmit antenna. For calculation of target tracking error, the joint Cramer Rao bound for a target velocity and position is computed and this is assumed as an objective function of the problem. It should be noted that a target RCS is also considered as unknown parameter and it is estimated along with target parameters. This makes a problem more similar to real conditions. After the investigation of the problem convexity, the problem is solved by particle swarm optimization (PSO) and sequential quadratic programming (SQP) algorithms. Then, various scenarios are simulated to evaluate the proposed scheme. The simulation results validate the accuracy and the effectiveness of the power allocation structure for target tracking in MIMO radar with widely separated antennas.

show abstract

“…To cope with complex targets and environments [4] and seek breakthroughs in target detection theory and technology [5], regime modification and resource management for radar are being continuously and intensively carried out [6][7][8]. Maximizing the cognitive operation capability [9,10], optimizing the utilization of available resources [11,12], and improving the target detection capability of radar systems are fundamental topics and practical and urgent tasks faced in the field of radar information processing and optimal resource management [13,14].…”

Section: Introductionmentioning

confidence: 99%

Optimal Configuration of Array Elements for Hybrid Distributed PA-MIMO Radar System Based on Target Detection

Xie

Zhang

et al. 2022

Remote Sensing

Self Cite

View full text Add to dashboard Cite

This paper establishes a hybrid distributed phased array multiple-input multiple-output (PA-MIMO) radar system model to improve the target detection performance by combining coherent processing gain and spatial diversity gain. First, the radar system signal model and array space configuration model for the PA-MIMO radar are established. Then, a novel likelihood ratio test (LRT) detector is derived based on the Neyman–Pearson (NP) criterion in a fixed noise background. It can jointly optimize the coherent processing gain and spatial diversity gain of the system by implementing subarray level and array element level optimal configuration at both receiver and transmitter ends in a uniform blocking manner. On this basis, three typical optimization problems are discussed from three aspects, i.e., the detection probability, the effective radar range, and the radar system equipment volume. The approximate closed-form solutions of them are constructed and solved by the proposed quantum particle swarm optimization-based stochastic rounding (SR-QPSO) algorithm. Through the simulations, it is verified that the proposed optimal configuration of the hybrid distributed PA-MIMO radar system offers substantial improvements compared to the other typical radar systems, detection probability of 0.98, and an effective range of 1166.3 km, which significantly improves the detection performance.

show abstract

Joint Antenna Placement and Power Allocation for Target Detection in a Distributed MIMO Radar Network

Cited by 7 publications

References 44 publications

Resource allocation scheme of netted radar system for target localisation

Resource allocation scheme of netted radar system for target localisation

A New Power Allocation Optimization for One Target Tracking in Widely Separated MIMO Radar

Optimal Configuration of Array Elements for Hybrid Distributed PA-MIMO Radar System Based on Target Detection

Contact Info

Product

Resources

About