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A novel method is proposed for asynchronous measurement fusion using maximum-likelihood (ML) estimator. This method is applied to multiple radar tracking and reconstruction of ballistic trajectories. The performance and robustness of the ML measurement fusion technique are analysed using a generic simulation scenario involving multi-sensor weapon locating in urban environment. Accuracies of firing point and impact point estimation of mortar grenades and artillery rockets are also evaluated taking into account different radars’ characteristics and geometries of the scenario. Immunity to glint noise, limited time of observation, and uncertainty of ballistic coefficient are also investigated. This study shows the effectiveness of the new method, advantages over track fusion approach, and reveals its practical value.

The paper is a follow-up to IRS 2015 submission “Multifunction C-Band Radar Development in Poland: Electronically Scanned Array Technology”. We briefly present various research, algorithms and results related to signal processing developed for Polish C-band radars.

The paper deals with the problem of state estimation of continuous-time nonlinear system using discrete-time measurements from multiple sensors. In particular, the problem of multi-radar tracking of artillery ballistic objects is considered. A batch estimator based on the iterative least squares approach is developed using simplified and accurate models of ballistic flight. The estimator is applied to process the sequences of measurements from radars tracking the same ballistic target. Estimates of the target state over time are computed and their accuracy is compared to the estimates yielded by the extended Kalman filter. Partial estimates from multiple radars are combined using track fusion approach and propagated using the 3 degree of freedom model of ballistic flight. Accuracy of target's firing point estimation is also analysed with respect to the data rates and locations of the radars with respect to the target. Practical aspects of the proposed method are also discussed.

In this paper radar technology developments in C band at PIT-RADWAR S.A. are presented. Research and development activities performed between 1990 and 2014 are briefly discussed and resulting technologies are presented and described.

The subject of this work is implementation of algorithms for classification and parametric identification of ballistic models based on radar measurements. This can involve different theoretical approaches and technical solutions. The choice of methods is discussed including mathematical models based on differential equations, numerical integration methods and non-linear optimisation techniques. In addition multi-thread programming techniques are applied in order to adapt implementation to modern multi-core processor architectures. Possibility of using specialised open-source libraries is also analysed with regard to technical aspects and taking into account the specificities of a commercial project and licensing conditions.

This paper deals with the problem of implementing adaptive radar tracking filters based on continuous-time models of target motion and on discrete-time models of measurement process. The particular difficulties addressed include: nonlinear and non-stationary target movement models with uncertain parameters, and low data rate due to a rotating radar antenna. The proposed tracking filter relies basically on the continuous-discrete variant of the extended Kalman filter (EKF), the probabilistic data association (PDA) technique and the interacting multiplemodel (IMM) state estimation scheme. Numerical properties of the algorithm are discussed and a software implementation is developed using the open-source BLAS library. Several design concepts are combined to assure numerical stability, convergence and efficiency of the estimator.

In this paper capabilities of target detection and tracking of bistatic receivers network cooperating with ATC radar are presented. Simulations are performed for different scenarios. A novel approach based on a modified hyperbolic approximation of target position is proposed that allow to improve the accuracy of radar measurements. The method appears efficient with three or more measurements available.

In this paper a problem of radar tracking of aircraft in medium-to-long range surveillance radars is considered. A mismatch is analysed that exists between the target movement model described in geodetic coordinates and typical model of motion in local Cartesian coordinates. In particular, the problem of estimating target course within the tracking filter using such local reference frame is analysed. Influence of the modelling mismatch on target course estimation is evaluated and quantified.

Urban areas constitute complex environments for radars. This paper deals with the problem of radar track formation for flying targets in low-level airspace over urban environment, particularly for artillery rockets and mortars. The presented experiments address the problem of sensitivity of two track formation algorithms, based on multisensor versions of the multiple hypothesis tracking approach (MHT) and the Hough transform, to radar performance degradation caused by urban environment. Simulation result show superiority of the MHT track initiator for virtually all performed tests. Moreover, multisensor detection can significantly reduce number of false alarms at the expense of only slight delay of track detection.

In this paper a problem of detection of tactical ballistic missiles (TBM) by a network of long-range air-defence radars (ADR) is addressed. Multi-radar detection capacity of TBM is evaluated using modelling and simulation techniques. The outcome of the study is shown in the form of the estimates of the signal-to-noise ratio (SNR), as would be observed at the outputs of the matched filters of the radars.