Introduction to the paper The presence of additive interference is one of the main problems of signal reception in radio systems [1-4]. At the same time, when we say about sources of interference which are located in space and have different angles-of-arrivals that signals of interest have, the most efficient way to deal with the problem of interference is using of spatial-temporal signal processing (STSP) [5-7]. The efficiency in current scope is the value of the ratio of the maximum allowable value of interference-to-signal ratio when the required accuracy of measurements is provided (vector of informative parameters).The use of STSP assumes involving an antenna array (AA) [8-10] and algorithms optimized in accordance with a particular criterion [11-13]. To achieve a high level of efficiency, the apparatus of statistical decision theory is usually used [15]. In this case the maximum likelihood (ML) is used as the optimisation criterion [15, 10]. The use of the ML criterion involves the calculation of the likelihood functions (LF) for the analyzed processes on the elements of the antenna array [10]. In the commonly known papers [11], the analytical form of the ML estimation algorithm contains interfering parameters , so that we have a case of composite hypotheses testing problem [15]. When the distribution of interfering parameters is unknown, their exclusion from the LF should be made in accordance to the generalized maximum likelihood criterion, which assumes the maximization of the LF by the unknown parameters [15]. Such maximization was dismissed in the mentioned papers, so that the given algorithm inapplicable in those practical situations when, for example, the initial phase and amplitude coefficient of the signal of interest are unknown. Let’s perform an analytical maximization of the LF for processes on the elements of AA by the interfering parameters of the signal (initial phase and amplitude coefficient), and estimate the efficiency of the synthesized ML algorithm by statistical modeling. To obtain upper bounds for the effectiveness of such approach, we first consider the case where the angles-of-arrival of both signal and interfering are precisely known.

Abstract for the Research Article The problem of low positioning accuracy in the presence of interference is discussed in this work. As a way to solve this problem spatial-temporal signal processing (STSP) is chosen when maximum likelihood (ML) optimisation criterion is used. The paper assumes that an interference is a Gaussian random process with a uniform (in the channel band) spectral noise density, and the additive components in each of the receiving channels are independent implementations of additive white Gaussian noise (AWGN). The commonly known form of likelihood function is transformed in the way to exclude interfering parameters of signal of interest. As a theoretical result ML-estimator of time-of-arrival was obtained. This results are supported by a statistical simulation so that the efficiency of synthesized ML algorithm is shown. At the end of the discussion the structure of navigation receiver implementation as an implications for practice is proposed.