Abstract
This paper proposes a subspace data fusion (SDF)-based direct positioning determination (DPD) method for noncircular sources with a moving nested array (NA). The DPD algorithms using a uniform linear array (ULA) and coprime (CP) array are available in the existing literature. Sparse arrays have larger apertures than ULAs, which enhances degrees of freedom (DOFs). However, the existing sparse CP arrays have limited DOF and also have poor detecting ability. In this paper, the physical sensors of NA are rearranged to obtain a difference sum NA (DSNA) and second-order super NA (II-SNA). The rearranged NA sensors are seen to increase array aperture. The noncircular characteristics of the sources are also used to improve accuracy in positioning. To obtain high DOF in NA, DSNA, and II-SNA, the covariance matrices are vectorized. The coherency of the virtual array is resolved by applying the spatial smoothing technique. Finally, the SDF-based DPD is used to establish the cost function and the target is localized. The simulation results are provided for the NA, DSNA, and II-SNA and are compared with the existing CP array DPD algorithm. The results show that the proposed method shows significant enhancement in localization accuracy. The Cramer-Rao lower bound (CRLB), complexity, and performance comparisons are also described in this paper.
Highlights
Passive source localization has been eliciting considerable interest in recent years and is an important area of array signal processing
To increase the degrees of freedom (DOF) of sparse arrays, Khatri Rao (KR) product is used for composing difference coarray (DC) with spatial smoothing-based multiple signal classification (MUSIC) algorithm
SIMULATION RESULTS This section presents the validation of the proposed method (DPD-Noncircular signals (NCS)-MDSNA) using numerical results
Summary
Passive source localization has been eliciting considerable interest in recent years and is an important area of array signal processing. To increase the DOF of sparse arrays, Khatri Rao (KR) product is used for composing difference coarray (DC) with spatial smoothing-based multiple signal classification (MUSIC) algorithm This method can be used to detect O(N 2). Difference and sum coarray (DSC) of NA (DSNA) give the extended physical aperture, by moving the dense sensors of NA to sparse sensors [27] This has many advantages including higher DOF, reduced redundancy, large physical aperture, and accuracy in the estimation of DOA with less mutual coupling. DPD method of strictly noncircular sources with a moving array was studied In this algorithm, data association problem in two-step localization was not encountered. This improves the estimation accuracy as this method has large array aperture In this proposed method, the difference and sum coarrays are obtained through vectorization and Kronecker product. The diag{.} constructs the diagonal matrix with all entries on its maindiagonal
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
