An effective PSO-based power allocation for target tracking in MIMO radar with widely separated antennas

Darzikolaei, Mohammad Akhondi; Mollaei, Mohammad Reza Karami; Najimi, Maryam

doi:10.1016/j.phycom.2021.101544

Cited by 11 publications

(8 citation statements)

References 23 publications

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“…In the case of random starting points and different KL divergence thresholds, the simulation results of CCCP are compared with the PSO algorithm used in [2,4] and the NP-Genetic Algorithm used in [7,8] to verify the effectiveness of the proposed algorithm. Furthermore, the influence of different parameter settings on the power allocation of the MIMO radar networking system could be analysed by the simulation results.…”

Section: Numerical Resultsmentioning

confidence: 99%

“…( 8) into the convex optimization problem to solve. The algorithm proposed in this paper is compared with the PSO algorithm used in [2,4] and the NPGA algorithm used in [6] in order to verify the effectiveness and KL divergence for each group are compared. For each group, the relationship between the total power of system and thr D is shown in Fig.…”

Section: Numerical Resultsmentioning

confidence: 99%

“…The issue of power allocation in radar networks has also attracted extensive attention. A particle swarm algorithm-based power allocation method is proposed by Darzikolaei, M. A. et al for MIMO radar, which can minimize target tracking errors under different antenna geometries [2]. Zhang, H. et al proposes a joint allocation strategy for power and bandwidth, which effectively improved the sum of weighted PCRLB for multiple targets by transforming the original problem into a two-step convex problem [3].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Power allocation optimization method for radar networking system based on sequential convex programming

Zhang

Tian

et al. 2023

International Conference on Signal Processing and Communication Technology (SPCT 2022)

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A power allocation model of MIMO radar networking system is proposed in this paper to meet the requirement of radio frequency stealth performance of airborne radar in modern warfare. Based on the KL divergence criterion and the SNR criterion, the model optimizes the transmitting power between the networked radars so as to minimize the total transmitting power of the system under the condition that the detection performance meets the threshold. Besides, the concave-convex-programming algorithm in sequential convex programming is used to solve the non-convex constrained optimization problem. The effectiveness of CCCP algorithm is verified by comparing with other heuristic algorithms.

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Section: Numerical Resultsmentioning

confidence: 99%

Section: Numerical Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Power allocation optimization method for radar networking system based on sequential convex programming

Zhang

Tian

et al. 2023

International Conference on Signal Processing and Communication Technology (SPCT 2022)

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“…The ISI was then reduced using a pulse shaping algorithm (PSA). Mohammed et al 19 studied the target tracking power allocation performance of MIMO radars with widely spread antennas. Initially, distributed antennas are used to build MIMO radar, and then the target movement is designed using the constant velocity (CV) technique.…”

Section: Literature Surveymentioning

confidence: 99%

Binomial distribution based grey wolf optimization algorithm for channel estimation in wireless communication system

Selvaraj,

Shanmugam,

Thangarajan

2023

Int J Communication

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SummarySeveral input high‐data‐rate transmissions over broadband wireless channels are possible using multiple input multiple output (MIMO) systems paired with orthogonal frequency division multiplexing (OFDM) technology. Channel estimation is an essential technique and a necessary component of MIMO‐OFDM systems. However, the noise will be there in MIMO‐OFDM due to the environment. As a result, the wireless system performs degrades in terms of bit error rate (BER). The suggested method offers a better pilot pattern strategy for MIMO‐OFDM and an efficient power allocation to address this issue. The binomial distribution‐based grey wolf optimization (BDGWO) algorithm is proposed to identify the optimal pilot patterns. The power is then adaptively distributed to each transmit antenna to increase the spectral efficiency and maximum channel capacity through an adaptive neuro‐fuzzy inference system with a sigmoid membership function (SMFANFIS). The best pilot patterns in PDGSIP (pilot design with generalized shift invariant property) were determined using the BDGWO algorithm based on the binomial distribution. According to the simulation results, the proposed BDGWO established pilot design with generalized shift invariant property (BDGWO‐DGSIP) achieves higher performance compared other existing approaches such as PDGSIP, TPDGSIP, and LS in terms of NMSE, BER, and SER. Compared to the PDGSIP technique, the proposed PDGSIP‐BDGWO system minimizes NMSE at 10%, BER at about 12%, and SER at 15%.

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“…Then with the iterative method, the problem is solved. The power allocation scheme based on PSO for one target tracking strategy is introduced in [16]. The problem is formed for MIMO radar with widely dispersed antennas.…”

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

Self Cite

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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.

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An effective PSO-based power allocation for target tracking in MIMO radar with widely separated antennas

Cited by 11 publications

References 23 publications

Power allocation optimization method for radar networking system based on sequential convex programming

Power allocation optimization method for radar networking system based on sequential convex programming

Binomial distribution based grey wolf optimization algorithm for channel estimation in wireless communication system

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

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