Multi-target direct positioning method based on neural network computing
A neural network and positioning method technology, which is applied in the field of multi-target direct positioning based on neural network computing, can solve problems such as large real-time computing load, and achieve the effect of reducing the number of samples
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Embodiment 1
[0087] Such as figure 1 As shown, a kind of multi-target direct positioning method based on neural network calculation of the present invention comprises the following steps:
[0088] Step S101: Construct L array output covariance matrices using the array signal data in L observation stations
[0089] Step S102: output the covariance matrix of L arrays Gather together and perform data preprocessing to get a real vector
[0090] Step S103: Divide the target area of interest into several sectors, and select a number of discrete position points in each sector, then use the selected discrete position points to construct learning data samples, and use the constructed learning data samples to train multi-layer front Feed the neural network;
[0091] Step S104: the real vector Input into the multilayer feed-forward neural network trained in step S103, to detect the number of targets in each sector, when multiple targets appear in a certain sector, the sector is further divi...
Embodiment 2
[0098] Such as figure 2 As shown, another kind of multi-target direct positioning method based on neural network calculation of the present invention comprises the following steps:
[0099] Step S201: Construct L array output covariance matrices using the array signal data in L observation stations include:
[0100] Step S2011: Assume that there are L static observation stations, and each observation station is equipped with an antenna array for locating the target, and there are D narrowband independent signal sources to be located that arrive at the array, and the array output signal model can be expressed as :
[0101]
[0102] where u d Indicates the position vector of the dth signal; a l (u d ) represents the array manifold vector generated by the dth signal arriving at the lth array; A l =[a l (u 1 ) a l (u 2 ) … a l (u D )] represents the manifold matrix corresponding to the lth array; s l (t)=[s l,1 (t)s l,2 (t) ... s l,D (t)] T Represents the sig...
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