Don't know if this is what you are trying to achieve, but during my limited testing I managed to deploy an extra notebook to a DLT pipeline to **only** stg by referencing it as an additional library:

targets:
  dev:
    default: true
    resources:
      pipelines:
        sales_pipeline:
          development: true

  stg:
    workspace:
      host: https://xxxx.x.azuredatabricks.net/ #Replace with the host address of your stg environment
    resources:
      pipelines:
        sales_pipeline:
          libraries:
          #Adding a Notebook to the DLT pipeline that tests the data
          - notebook:
              path: "./50_tests/10_integration/DLT-Pipeline-Test.py"
          development: true

  prod:
    workspace:
      host: https://xxx.x.azuredatabricks.net/ #Replace with the host address of your prod environment
    resources:
      pipelines:
        sales_pipeline:
          development: false
          #Update the cluster settings of the DLT pipeline
          clusters:
            - autoscale:
                min_workers: 1
                max_workers: 2

The actual asset is deployed to all targets, but the pipeline in where it is referenced and ran is target specific. 

More info and source code here if you want to test: ossinova/databricks-asset-bundles-demo: A demo of using databricks asset bundles (github.com)