- مبلغ: ۸۶,۰۰۰ تومان
- مبلغ: ۹۱,۰۰۰ تومان
The direct position determination (DPD) approach is a single-step method which uses the Maximum Likelihood estimator to localize sources emitting electromagnetic energy using combined data from all available sensors. The DPD is known to outperform the traditional 2-step methods under low Signal to Noise Ratio (SNR) conditions. We propose an improvement to the DPD approach, using the well known minimum-variancedistortionless-response (MVDR) approach. Unlike Maximum Likelihood, the number of sources need not be known before applying the method. The combination of both the direct approach and MVDR yields unprecedented localization accuracy and resolution for weak sources. We demonstrate this approach on the problem of multistatic radar, but the method can easily be extended to general localization problems.
In this paper we proposed a single-step direct position determination (DPD) using the MVDR approach rather than the single target Maximum Likelihood approach. The proposed method is an adaptive method, using the returns from several consecutive pulses for computation of the target’s location directly without first estimation of direction of arrival and delay. We presented DPD based on single target Maximum Likelihood and DPD based on MVDR for multistatic radar, but our approach may easily be extended to other localization problems. We demonstrated that the MVDR approach achieves superior resolution with respect to the Maximum Likelihood by analyzing multiple near targets localization. The targets used in the analysis can represent a single target with multiple, resolvable scatterers or represent separate, small targets. The fine resolution can be employed to resolving real targets from many decoys.