J-Mate is a new, atypically device and people will look at it with some skepticism asking themselves about the laser behavior in a forest environment with dense foliage/pines also difficult enough for any LS-like receiver. But J-Mate can do more, I think..
Measuring a wooded trench (picture 1), 30-50m away from the forest clearing, is not an easy task. If the trench is straight, I can make some offsets from the open area using my receiver, but with changing directions, it becomes more difficult. A dense forest with spikes and branches could challenge even the LS and J-Mate with laser. Almost certainly the crew will lose time, cutting and dialoguing... (1-2, 3-4, 5-6-7).
From my point of view, I can hear the guys making all kind of "spread spectrum" sounds in the canopy. I can also differentiate the persons and make a coarse estimation of their positions. But I can't see them. In the same way, with a proper device, the position of a stationary subject (as far as I know) can be estimated with accuracy around 20-30 mm from 30-40m distance using spread spectrum sounds.
Probably, with some narrow-beam microphone attached to J-Mate, a distance could be calculated by measuring the time of flight of the sound wave from the subject and then multiplying it by the sound velocity, for a better positioning. And the correct distance will indicate the correct azimuth for J-Mate. Maybe a better alternative when cellular doesn't work, a base-rover solution could be expensive and cutting could take most of the day work.
Next picture shows a 30 years old property line in the older dense forest and the newly grown forest (30-50m width) that is beautiful, but is a nightmare for every surveyor and a much more capable robotic total station will be blind in a dense foliage/pines environment.
In real life, there are many factors that need to be taken into account, such as temperature gradient, wind, background noise and the presence of obstacles, but I imagine J-Target (or the phone) with sound capabilities and J-Mate + LS estimating signal sounds, with multiple engines and built-in, real-time spectrum analyzer.
Anyway, for me this is just a suggestion, but when it comes to signals, Javad team is the right choice. They create things which seem impossible to others..