he backward model utilizes either near-field or far-field recordings to extractsound source signals. Compared to the forward model, undertaking measurementsconsumes much more time. Nevertheless, it saves the time to establish physical orempirical models. Moreover, synthesis from recordings overcomes the deficiency oflow realism which is probably the main drawback of the forward model. Arntzenet al. [11] concluded that the synthesized sounds of aircraft flyovers were perceiveddifferently compared to the measurements due to the empirical source models.Similar results were reported when auralization was implemented in form of aweb-based virtual reality (VR) tool, which synthesized signals based on forwardmodelling, resulting in artificial perception [19]. More problematically, theoreticalmodels or empirical equations are not always achievable.In [20], sound samples were extracted by analyzing near-field recordings of an en-gine running at various speeds. Target sounds were synthesized by concatenatingcorresponding samples with an overlap and add algorithm in real time. Addition-ally, in previous work, the synthesized signals were compared and validated withthe original signals [6]. Validation using the backward model is more convenientsince synthesized signals are obtained from measurements and thus comparisoncan be directly conducted after synthesis, whereas the forward model addition-ally needs specific validation measurements. A model for synthesizing electricalrailbound vehicles was suggested by Klemenz [21]. In this model, rolling noiseand air conditioner noise were added directly from recordings, while the tonaltraction noise components were synthesized by simple calculations of sinusoidsand sweeps. If no near-field recordings are available, the backward model is needed to computesource signals from far-field recordings. For example, aerodynamic noise, causedby high-speed motion, is only possible to be measured at a comparatively largedistance from the moving object. In this sense, the backward model can alsobe called inverse model. An aircraft auralization model was established usingmicrophone recordings based on a backward sound propagation model [22,23].For an aircraft, the sound source can be considered as one point source due to thelarge measurement distance.