Distributed radar multi target tracking based on range-Doppler measurements

Baruzzi, Aurora; Pasculli, Davide

doi:10.1109/iceaa.2013.6632282

Cited by 3 publications

(9 citation statements)

References 3 publications

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“…It is possible to observe the capability of the algorithm to correctly estimate the position of the target with a mean square error (MSE) value of about 4.5%. As explained accurately in [3], during the pre-tracking stage we have to tolerate an error in terms of distance and speed due to the centroids estimation. In this case, the errors are approximately 1–2 m and 0.2 m/s.…”

Section: Resultsmentioning

confidence: 99%

“…First of all an algorithm for transforming RD coordinates into Cartesian coordinates has been developed. It consists of a series of operations which are described in detail in [3].…”

Section: Trackingmentioning

confidence: 99%

“…It is made up of four active high-resolution radars whose parameters of interest are summarized up in Table 1. The target used in the simulations, a Swerling I target model, is a ship [3], made of about 2000 scatterers. Since the radars used have high-resolution, the target will appear in more than one resolution cell.…”

Section: Simulation Analysismentioning

confidence: 99%

“…With respect to previous work [3], a study of a model for the sea clutter has been carried out and simulated sea clutter has been added to the simulated received signal. This has been done in order to test the robustness of the proposed algorithm in a more realistic scenario since real data is not available yet.…”

Section: Introductionmentioning

confidence: 99%

“…This has been done in order to test the robustness of the proposed algorithm in a more realistic scenario since real data is not available yet. The algorithm has also been tested in conditions of nearly constant acceleration (nCA) [4–6] instead of the more limiting scenario of nearly constant velocity (nCV) [3].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Multi-sensor multi-target tracking based on range-Doppler measurement

Baruzzi

2015

Int. J. Microw. Wireless Technol.

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In this paper, we present a method for multiple target two-dimensional tracking using multiple sensors with very low azimuth resolution. Due to the scarce azimuth resolution, the data association is performed using range and Doppler information only from four radars. The proposed algorithm is tailored to perform in maritime scenarios. In order to test the algorithm perform- ance, sea clutter data have been taken under consideration when simulating data

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Section: Resultsmentioning

confidence: 99%

“…First of all an algorithm for transforming RD coordinates into Cartesian coordinates has been developed. It consists of a series of operations which are described in detail in [3].…”

Section: Trackingmentioning

confidence: 99%

Section: Simulation Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Multi-sensor multi-target tracking based on range-Doppler measurement

Baruzzi

2015

Int. J. Microw. Wireless Technol.

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Multi-Target Tracking Algorithm Based on 2-D Velocity Measurements Using Dual-Frequency Interferometric Radar

Ishtiaq¹,

Wang²,

Hassan³

2021

Electronics

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Multi-target tracking (MTT) generally requires either a network of Doppler radar receivers distributed at different locations or a phased array radar. The targets moving with small/no radial velocity or angular velocity only cannot be detected and localized completely by deploying Doppler radar without antenna arrays or multiple receivers. To resolve this issue, we present a new MTT algorithm based on 2-D velocity measurements, namely, radial and angular velocities, using dual-frequency interferometric radar. The contributions of the proposed research are twofold: First, we introduce the mathematical model and implementation of the proposed algorithm by explicitly establishing the relationship between 2-D velocity measurements and kinematic state of the target in terms of Cartesian coordinates. Based on 2-D velocity measurement function, the proposed MTT algorithm comprises the following steps: (i) data association using global nearest neighbor (GNN) method (ii) target state estimation using interacting multiple model (IMM) estimator combined with square-root cubature Kalman filter (SCKF) (iii) track management using rule-based M/N logic. Second, performance of the proposed algorithm is evaluated in terms of tracking accuracy, computational complexity and IMM mean model probabilities. Simulation results for different scenarios with multiple targets moving in different tracks have been presented to verify the effectiveness of the proposed algorithm.

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Three-Dimensional Multi-Target Tracking Using Dual-Orthogonal Baseline Interferometric Radar

Ishtiaq

Wang

Hassan

et al. 2022

Sensors

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Multi-target tracking (MTT) generally needs either a Doppler radar network with spatially separated receivers or a single radar equipped with costly phased array antennas. However, Doppler radar networks have high computational complexity, attributed to the multiple receivers in the network. Moreover, array signal processing techniques for phased array radar also increase the computational burden on the processing unit. To resolve this issue, this paper investigates the problem of the detection and tracking of multiple targets in a three-dimensional (3D) Cartesian space based on range and 3D velocity measurements extracted from dual-orthogonal baseline interferometric radar. The contribution of this paper is twofold. First, a nonlinear 3D velocity measurement function, defining the relationship between the state of the target and 3D velocity measurements, is derived. Based on this measurement function, the design of the proposed algorithm includes the global nearest neighbor (GNN) technique for data association, an interacting multiple model estimator with a square-root cubature Kalman filter (IMM-SCKF) for state estimation, and a rule-based M/N logic for track management. Second, Monte Carlo simulation results for different multi-target scenarios are presented to demonstrate the performance of the algorithm in terms of track accuracy, computational complexity, and IMM mean model probabilities.

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Distributed radar multi target tracking based on range-Doppler measurements

Cited by 3 publications

References 3 publications

Multi-sensor multi-target tracking based on range-Doppler measurement

Multi-sensor multi-target tracking based on range-Doppler measurement

Multi-Target Tracking Algorithm Based on 2-D Velocity Measurements Using Dual-Frequency Interferometric Radar

Three-Dimensional Multi-Target Tracking Using Dual-Orthogonal Baseline Interferometric Radar

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